Microwave perception-based electric tower settlement monitoring and early warning method and system

Abstract

The present application relates to the technical field of power facility monitoring, in particular to a method and system for monitoring and early warning of tower settlement based on microwave sensing, the method comprising analyzing the operation mismatch condition of the microwave sensing device, adjusting the microwave sensing device to obtain an adjusted microwave sensing device; monitoring the tower and collecting information by the adjusted microwave sensing device to obtain a tower monitoring information database; extracting a baseband signal set of the tower monitoring point from the tower monitoring information database, and obtaining distance-angle dimension parameter information of the tower monitoring point, analyzing the total displacement prediction result of the tower according to the distance-angle dimension parameter information and the signal set; comparing and analyzing the tower settlement condition in combination with the settlement monitoring early warning mechanism, the total displacement prediction result and the information database to obtain the tower settlement analysis result. The present application predicts and analyzes the tower displacement condition based on microwave sensing information, realizes real-time monitoring and intelligent early warning of the tower settlement condition.

Description

Technical Field

[0001] This invention relates to the field of power facility monitoring technology, specifically to a method and system for monitoring and early warning of power tower settlement based on microwave sensing. Background Technology

[0002] During power transmission, power towers are highly susceptible to settlement due to various factors. Unforeseen events such as landslides and geological disasters can directly damage the geological structure of the area where the tower is located, leading to tower settlement. Dynamic changes in groundwater, such as water level fluctuations and erosion, can alter geological conditions, ultimately causing tower settlement. Once power towers settle, they pose serious safety hazards to the power grid and cause significant inconvenience and losses to social production and daily life.

[0003] Traditional methods of power tower inspection have significant limitations. First, traditional inspections are insufficient to achieve comprehensive coverage of power towers in remote areas, making it difficult to detect tower settlement in a timely manner. Second, traditional monitoring methods rely mainly on inspection experience and periodic checks, making it difficult to capture sudden settlement risks in real time and to take timely countermeasures in the early stages of settlement.

[0004] Furthermore, tower settlement is influenced by a variety of factors, including geological conditions, climate, and construction techniques, resulting in complex and variable development patterns with inherent uncertainties and hidden characteristics. Traditional data monitoring methods suffer from low information monitoring accuracy, untimely data transmission, and inaccurate monitoring results, making it impossible to achieve digital management of tower monitoring information and hindering real-time monitoring and timely early warning of tower settlement.

[0005] Therefore, a method is needed to accurately monitor the micro-motion changes of power towers and obtain effective information, realize the digital transmission and effective management of power tower monitoring information, and intelligently monitor and accurately predict the settlement of power towers, thereby enabling the identification of tower base settlement risks and safety early warning, and further ensuring the safe and stable operation of the power grid. Summary of the Invention

[0006] To address the shortcomings of existing methods and meet the needs of practical applications, in order to effectively monitor and obtain relevant information on the micro-motion changes of power towers, relevant algorithms are used to analyze and predict the condition and settlement status of power towers, thereby achieving accurate identification and timely early warning of power tower settlement risks, and further ensuring the safe and stable operation of the power grid. On the one hand, this invention provides a method for monitoring and early warning of power tower settlement based on microwave sensing. The method includes: analyzing the operational mismatch of microwave sensing equipment, adjusting the microwave sensing equipment according to the operational mismatch, and obtaining the adjusted microwave sensing equipment; deploying the adjusted microwave sensing equipment, monitoring and collecting information about the power tower through the adjusted microwave sensing equipment to obtain a power tower monitoring information database; extracting the baseband signal set of the power tower monitoring points from the power tower monitoring information database, obtaining the distance-angle dimension parameter information of the power tower monitoring points based on the baseband signal set, analyzing the total displacement prediction result of the power tower based on the distance-angle dimension parameter information and the baseband signal set; constructing a settlement monitoring and early warning mechanism, and comparing and analyzing the power tower settlement situation by combining the settlement monitoring and early warning mechanism, the total displacement prediction result, and the power tower monitoring information database to achieve real-time monitoring and intelligent early warning of power tower settlement.

[0007] This invention makes targeted adjustments to the microwave sensing equipment, enabling it to better adapt to the actual environment and working requirements of power tower monitoring. This helps improve the accuracy and reliability of data acquisition and provides basic data for subsequent power tower status analysis. By analyzing the total displacement prediction results of the power tower based on multi-dimensional parameter information and signal processing algorithms, the displacement trend of the power tower can be predicted more accurately, which helps to detect potential settlement problems of the power tower in advance.

[0008] Optionally, the analysis of the operational mismatch of the microwave sensing device includes: analyzing the incident power and reflected power of the signal based on the structural information of the microwave sensing device; obtaining the actual load power of the microwave sensing device based on the incident power and the reflected power; constructing a mismatch loss calculation formula based on the actual load power; obtaining the mismatch loss result of the microwave sensing device through the mismatch loss calculation formula; and analyzing the load impedance mismatch of the microwave sensing device based on the mismatch loss result.

[0009] This invention obtains the actual load power by measuring the incident and reflected power of the signal, which allows for a clear understanding of the power consumption of the microwave sensing device under different operating conditions. Further adjustments can be made to the device to ensure stable operation at optimal power, thereby improving the device's operating efficiency.

[0010] Optionally, the analysis of operational mismatch in the microwave sensing device includes: standardizing and defining the signal source and load parameters of the microwave sensing device and obtaining parameter definition information; establishing a power transfer equation based on the microwave signal reflection of the microwave sensing device; optimizing the power transfer equation based on the parameter definition information to obtain a power transfer analysis expression; and analyzing the mismatch between the signal source and load impedance using the power transfer analysis expression and the parameter definition information.

[0011] This invention adjusts the signal source and load impedance to keep the device in good condition, which can reduce signal reflection during transmission, reduce signal distortion and interference, and thus ensure stable signal transmission.

[0012] Optionally, adjusting the microwave sensing device based on the operational mismatch and obtaining the adjusted microwave sensing device includes: combining... The matching network and the load impedance mismatch condition transform the load impedance of the microwave sensing device to obtain a load impedance that matches the transmission line impedance; the circuit parameters, impedance network, and phase offset of the microwave sensing device are adjusted according to the mismatch condition between the signal source and the load impedance to obtain a characteristic impedance close to the transmission line, an adapted impedance network, and a compensated offset factor; the adjusted microwave sensing device is obtained based on the load impedance, the characteristic impedance, the adapted impedance network, and the compensated offset factor.

[0013] The microwave sensing device adjusted by this invention has more stable impedance matching and signal transmission characteristics, can better resist external interference, reduces the impact of external interference on the monitoring signal, improves the anti-interference capability of the microwave sensing device, and ensures that the device can work stably in various environments.

[0014] Optionally, the deployment of the adjusted microwave sensing device, and the monitoring and information collection of the power tower through the adjusted microwave sensing device to obtain a power tower monitoring information database, includes: deploying the adjusted microwave sensing device based on the actual environmental conditions; selecting key monitoring locations of the power tower based on the actual environmental conditions; setting information monitoring points during the power tower settlement monitoring process based on the key monitoring locations; and monitoring and collecting information from the power tower according to the information monitoring points and the adjusted microwave sensing device to obtain a power tower monitoring information database.

[0015] This invention selects key monitoring locations for power towers based on the actual environment, ensuring that monitoring points cover critical parts of the power towers and areas prone to problems. This allows for more accurate detection of minute changes in the power towers, timely discovery of potential safety hazards, and provides data support for subsequent analysis and decision-making.

[0016] Optionally, the step of extracting the baseband signal set of the power tower monitoring points from the power tower monitoring information database includes: obtaining channel information, signal amplitude, phase information, and frequency data of a single information monitoring point based on the power tower monitoring information database; analyzing the baseband signal of a single information monitoring point based on the channel information, the signal amplitude, the phase information, and the frequency data; and integrating and analyzing the baseband signal of the single information monitoring point to construct information, so as to obtain the baseband signal set of the power tower monitoring points.

[0017] This invention obtains channel information, signal amplitude, phase information, and frequency data of a single information monitoring point from the power tower monitoring information database, enabling a comprehensive understanding of the signal characteristics of the monitoring point and a full-scale analysis of the signal at the power tower monitoring point, thus allowing for a more accurate grasp of the power tower's operating status at that monitoring point.

[0018] Optionally, obtaining the distance-angle dimension parameter information of the power tower monitoring point based on the baseband signal set includes: performing a two-dimensional Fourier transform on the baseband signal set to obtain distance dimension transform information and angle dimension transform information; obtaining a distance dimension phase rotation factor based on the distance dimension transform information; obtaining an angle dimension phase rotation factor based on the angle dimension transform information; and obtaining the distance-angle dimension parameter information of the power tower monitoring point based on the distance dimension transform information, the angle dimension transform information, the distance dimension phase rotation factor, and the angle dimension phase rotation factor.

[0019] The distance-angle dimension parameter information of this invention can be integrated with other types of monitoring data to provide more comprehensive information for the integrated monitoring and evaluation of power towers, and to provide information basis for the evaluation of power tower structures.

[0020] Optionally, the step of analyzing the total displacement prediction result of the power tower based on the distance-angle dimension parameter information and the baseband signal set includes: establishing a phase analysis formula for monitoring points within a fixed period based on the distance-angle dimension parameter information; analyzing the phase analysis results of different information monitoring points within a fixed sweep frequency period using the phase analysis formula for monitoring points within the fixed period; constructing a monitoring point displacement prediction function by combining the information monitoring points in the power tower settlement monitoring process and the phase analysis results; obtaining the displacement analysis results of different information monitoring points using the monitoring point displacement prediction function and the baseband signal set; integrating the displacement analysis results of different information monitoring points to analyze the power tower displacement and obtain the total displacement prediction result of the power tower.

[0021] This invention establishes a phase analysis formula for monitoring points within a fixed period, and uses the formula to analyze the phase of different information monitoring points within a fixed frequency sweep period. This enables phase information processing of monitoring points to be completed in a short time, which is beneficial for real-time monitoring and accurate prediction of power tower displacement.

[0022] Optionally, the construction of the settlement monitoring and early warning mechanism, which combines the settlement monitoring and early warning mechanism, the total displacement prediction results, and the power tower monitoring information database to compare and analyze the power tower settlement situation to achieve real-time monitoring and intelligent early warning of power tower settlement, includes: setting a settlement benchmark threshold and a graded evaluation mechanism in the settlement monitoring and early warning mechanism; dynamically comparing and analyzing the displacement analysis results of different information monitoring points and the total displacement prediction results based on the settlement benchmark threshold and the graded evaluation mechanism to obtain the power tower settlement analysis results; issuing safety early warning information on power tower settlement by combining the safety early warning device in the settlement monitoring and early warning mechanism, the power tower settlement analysis results, and the power tower monitoring information database; and realizing real-time monitoring and intelligent early warning of power tower settlement based on the safety early warning information.

[0023] Based on a settlement benchmark threshold and a graded evaluation mechanism, this invention dynamically compares and analyzes the displacement analysis results and total displacement prediction results of different information monitoring points. This allows for a more comprehensive understanding of the settlement status of the power tower, reduces misjudgments caused by abnormal data from individual monitoring points or prediction errors, and thus improves the accuracy of the power tower settlement analysis results.

[0024] Secondly, in order to efficiently execute the microwave sensing-based power tower settlement monitoring and early warning method provided by this invention, this invention also provides a microwave sensing-based power tower settlement monitoring and early warning system. The system includes an input device, a processor, an output device, and a memory, wherein the input device, processor, output device, and memory are interconnected. The memory is used to store a computer program, which includes program instructions. The processor is configured to call the program instructions to jointly execute the microwave sensing-based power tower settlement monitoring and early warning method as described in the first aspect of this invention. The microwave sensing-based power tower settlement monitoring and early warning system provided by this invention has a compact structure, strong applicability, and greatly improves operating efficiency. Attached Figure Description

[0025] Figure 1 This is a flowchart of the microwave sensing-based method for monitoring and early warning of power tower settlement according to the present invention.

[0026] Figure 2 This is a structural diagram of the microwave sensing-based power tower settlement monitoring and early warning system of the present invention. Detailed Implementation

[0027] Specific embodiments of the present invention will now be described in detail. It should be noted that the embodiments described herein are for illustrative purposes only and are not intended to limit the invention. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the invention. However, it will be apparent to those skilled in the art that these specific details are not necessary to practice the invention. In other instances, well-known circuits, software, or methods have not been specifically described to avoid obscuring the invention.

[0028] Throughout this specification, references to "an embodiment," "an embodiment," "an example," or "an example" mean that a particular feature, structure, or characteristic described in connection with that embodiment or example is included in at least one embodiment of the invention. Therefore, the phrases "in an embodiment," "in an embodiment," "an example," or "an example" appearing in various places throughout the specification do not necessarily refer to the same embodiment or example. Furthermore, specific features, structures, or characteristics can be combined in one or more embodiments or examples in any suitable combination and / or sub-combination. Moreover, those skilled in the art will understand that the illustrations provided herein are for illustrative purposes and are not necessarily drawn to scale.

[0029] Please see Figure 1 To effectively monitor the micro-motion changes of power towers and obtain relevant data, this invention constructs a specific algorithm to analyze the changing trends and settlement status of power towers, conducts comparative analysis and identification of power tower settlement risks, and provides a power tower settlement monitoring and early warning method based on microwave sensing. The method includes the following steps:

[0030] S1. Analyze the operational mismatch of the microwave sensing equipment, adjust the microwave sensing equipment according to the above operational mismatch, and obtain the adjusted microwave sensing equipment. The specific setup steps and implementation content are as follows:

[0031] To improve the measurement accuracy of microwave sensing equipment, it is necessary to analyze the measurement error of the equipment and make targeted adjustments to the microwave sensing equipment based on the error situation and mismatch, so as to obtain microwave sensing equipment with better performance.

[0032] The microwave sensing device in this embodiment mainly consists of several key components, including a signal source (signal generator), a transmission line, and a load (such as a power meter, spectrum analyzer, etc.). In an ideal operating environment, the impedance values ​​of the signal source, transmission line, and load are all set to... Together, these three components form an impedance matching module that ensures efficient and stable transmission and processing of microwave signals.

[0033] However, in real-world applications, the actual effective value of the impedance of the aforementioned components is not fixed but fluctuates and changes to some extent. This impedance instability can cause mismatch in microwave sensing equipment during operation, ultimately leading to data measurement errors and affecting the accuracy of tower monitoring information. The following analysis will address different mismatch scenarios and implement corresponding adjustment measures.

[0034] During the operation of microwave sensing equipment, a mismatch between the load impedance and the transmission line impedance can cause signal reflection, thereby affecting the measurement accuracy and performance of the equipment. To accurately analyze the operational mismatch of microwave sensing equipment, a detailed analysis can be performed according to the following steps:

[0035] I. Analyze the operational mismatch of microwave sensing equipment.

[0036] The first step is to analyze the incident power and reflected power of the signal based on the configuration information of the microwave sensing equipment.

[0037] Since microwave sensing equipment mainly consists of a signal source (signal generator), transmission lines, and loads (power meters, spectrum analyzers, etc.), during signal transmission, the signal source emits an incident voltage. This voltage is transmitted along the transmission line to the load. When it reaches the load, if the load impedance and the characteristic impedance of the transmission line are different... When there is a mismatch, part of the voltage will be reflected back, forming a reflected voltage. The reflected voltage will be absorbed and returned to the signal source. If the signal source is in an ideally matched state, the reflected voltage will be completely absorbed and will not be reflected again.

[0038] Incident power traveling toward the load It satisfies the following calculation formula:

[0039]

[0040] in, Indicates incident power. Indicates the incident voltage. This represents the characteristic impedance of the transmission line. This formula shows that the incident power is proportional to the square of the incident voltage and to the characteristic impedance of the transmission line. Inversely proportional, incident power reflects the amount of power transmitted from the signal source to the load.

[0041] Power reflected by the load The calculation formula is as follows:

[0042]

[0043] in, Indicates reflected power. Indicates the reflected voltage. This represents the characteristic impedance of the transmission line. This represents the reflection coefficient. Reflected power is the power carried by the reflected signal due to load impedance mismatch.

[0044] The above reflection coefficients satisfy the following conditions This reflects the degree of matching between the load impedance and the transmission line impedance, and its value range is... .when When the load and transmission line are perfectly matched, there is no reflected power. ;when When this occurs, it indicates a complete mismatch between the load and the transmission line, and the reflected power reaches its maximum value in the city. .

[0045] The second step is to obtain the actual load power of the microwave sensing device based on the incident power and reflected power.

[0046] Actual power obtained on the load The difference between the incident power and the reflected power is:

[0047]

[0048] Will Substituting into the above formula, we get:

[0049]

[0050] And because Furthermore, we can obtain:

[0051]

[0052] in, This indicates the actual power received by the load.

[0053] The above formula clearly shows that the actual power received by the load is related to the incident power and the square of the reflection coefficient. The larger the reflection coefficient, the smaller the actual power received by the load, especially when the load is perfectly matched to the transmission line. When the load is completely mismatched with the transmission line, the actual power received by the load is at its maximum, equal to the incident power; when the load is completely mismatched with the transmission line... When ), the actual power received by the load is 0.

[0054] The third step is to construct a formula for calculating mismatch loss based on the actual power of the load.

[0055] Since the incident power is not fully absorbed by the load due to load mismatch, the resulting mismatch loss is calculated according to the following formula:

[0056]

[0057] in, Indicates mismatch loss. This indicates the actual power received by the load. This indicates the incident power.

[0058] Bundle Substituting, we get:

[0059]

[0060] in, Indicates mismatch loss. This represents the reflection coefficient.

[0061] In this embodiment, the unit of mismatch loss is decibels (dB), which can intuitively reflect the degree of impact of load impedance mismatch on power transmission. The greater the mismatch loss, the worse the matching degree between the load impedance and the transmission line impedance.

[0062] Furthermore, measurement errors exist in the actual measurement process. Let the measured reflection coefficient be... The actual reflection coefficient is Introducing measurement error coefficient And satisfy:

[0063]

[0064] in, This represents the measured value of the reflection coefficient. Indicates the measurement error coefficient. This represents the actual value of the reflection coefficient, as stated above. The range of values ​​is within The specific value can be adjusted and determined based on the accuracy of the actual measuring equipment.

[0065] Based on this, the formula for calculating mismatch loss is optimized to obtain the optimized mismatch loss. And it satisfies the following relationship:

[0066]

[0067] Will Substituting into the above formula, we get:

[0068]

[0069] in, This represents the optimized mismatch loss. Indicates the measurement error coefficient. This represents the measured value of the reflection coefficient. This represents the actual value of the reflection coefficient.

[0070] Measurement error coefficient It is mainly used to correct the measured reflection coefficient to improve the accuracy of the mismatch loss calculation results. At the same time, the introduction of a measurement error coefficient makes the mismatch loss calculation closer to the actual situation and reduces the impact of measurement errors on the analysis results.

[0071] The fourth step is to obtain the mismatch loss result of the microwave sensing device through the mismatch loss calculation formula.

[0072] Substitute the actual measured reflection coefficient (or the reflection coefficient determined based on actual conditions and calculated using the measurement error coefficient) into the optimized mismatch loss calculation formula. The mismatch loss of the microwave sensing device can be obtained through calculation.

[0073] The fifth step is to analyze the load impedance mismatch of the microwave sensing equipment based on the mismatch loss results.

[0074] In an alternative embodiment, if the mismatch loss is small This indicates that the load impedance and transmission line impedance are well matched, the reflection coefficient is close to 0, the load can effectively absorb the incident power, the equipment is in an ideal operating state, and the measurement error has little impact on the results.

[0075] If the mismatch loss is moderate This indicates a certain mismatch between the load impedance and the transmission line impedance, causing the reflection coefficient to fluctuate within a certain range. In this case, the microwave sensing device can still function normally, but it will have a certain impact on the measurement accuracy. It is necessary to pay close attention to the changes in the load impedance and make appropriate adjustments when necessary.

[0076] If the mismatch loss is large This means that the load impedance and the transmission line impedance are severely mismatched, and the reflection coefficient is close to... Most of the incident power is reflected back, and the actual power received by the load is very small. In this situation, the measurement accuracy of the microwave sensing equipment will be significantly affected, and it is necessary to immediately check the connection of the load and transmission line and take appropriate measures to adjust it.

[0077] By following the above five steps, we can gain a comprehensive and accurate understanding of the operational mismatch of microwave sensing equipment, providing a reference and direction for equipment optimization, adjustment, and performance improvement.

[0078] II. Analysis of operational mismatches in microwave sensing equipment.

[0079] During the operation of microwave sensing equipment, the mismatch between the signal source and the load impedance can cause signal reflection, which in turn affects the performance and measurement accuracy of the equipment. The following steps will be used to investigate this issue.

[0080] The first step is to standardize and define the signal source and load parameters of the microwave sensing device, and obtain the parameter definition information.

[0081] In order to comprehensively and accurately analyze the signal source and load mismatch scenario and quantify the impact of phase uncertainty on power transmission, the relevant parameters of the microwave sensing device are standardized and defined in this embodiment.

[0082] The signal source reflection coefficient is defined as ,in Represents the signal source reflection coefficient. Indicates the actual output impedance of the signal source. This represents the characteristic impedance of the transmission line. This coefficient reflects the degree of matching between the output impedance of the signal source and the characteristic impedance of the transmission line, and its value ranges from [value range missing]. Between, when When the signal source output impedance is perfectly matched with the characteristic impedance of the transmission line; when "Time" indicates a complete mismatch.

[0083] Load reflection coefficient is defined as ,in, Indicates the load reflection coefficient. The actual impedance of the load. This represents the characteristic impedance of the transmission line. This coefficient reflects the matching between the load impedance and the characteristic impedance of the transmission line, and its value range is also within [range missing]. between, This indicates that the load and transmission line are perfectly matched. This indicates a complete mismatch.

[0084] The double-ended coupling reflection coefficient is defined as ,in The double-ended coupling reflection coefficient represents the intensity of the round-trip reflection of a signal between the source and the load. This coefficient combines the reflection characteristics of the signal source and the load, reflecting the degree of coupling between them.

[0085] The phase shift factor can be measured using a vector network analyzer. Phase shift factor The phase angle is related to the reflection coefficients of the signal source and the load. By measuring this, the maximum / minimum power transmission boundary can be calculated, thus providing a more comprehensive understanding of the phase changes of the signal during transmission.

[0086] The second step is to establish a power transfer equation based on the microwave signal reflection of the microwave sensing device.

[0087] When the signal source and load impedances are mismatched, the signal reflected from the load will not be absorbed after returning to the signal source, but will be reflected back to the load again. The relevant reflected signals may superimpose or cancel each other out at the load, depending on the signal phase. In the case of a slight mismatch between the signal source and load impedances, the amplitude of each additional reflection is much smaller than the first round-trip reflection between the load and the signal source. Therefore, this embodiment only considers the first round-trip reflection.

[0088] Incident wave signal source voltage The signal propagates from the source to the load, generating an incident voltage at the load. After the voltage is reflected back to the signal source, it is reflected again to the load, forming a second incident wave. At this time, there are two incident waves on the load, and the following relationship exists:

[0089]

[0090] Therefore, we can conclude that:

[0091]

[0092] The uncertainty of the sign of the reflection term indicates the uncertainty of whether the reflected waves are superimposed or canceled out.

[0093] The above Taking the square and combining it with the mismatch loss at the signal source and load, we can obtain the power transfer equation, which satisfies the following relationship:

[0094]

[0095] The numerator of the power transfer equation This reflects the impact of mismatch loss, indicating that a given reflection coefficient will lead to a corresponding power loss in the load; the denominator This represents the uncertainty of the mismatch. Power transfer is uncertain due to the positive or negative sign of the denominator, and the actual power transfer may fall between two extreme cases. From a measurement perspective, obtaining the maximum and minimum power transfer can clearly identify the maximum and minimum errors that may arise due to impedance matching issues.

[0096] Logarithmic analysis of the power transfer equations facilitates the subsequent individual consideration of each error term, leading to the following:

[0097]

[0098] Then, according to the logarithmic multiplication rule ,right Expanding it yields ;

[0099] At the same time, according to the power law of logarithms ,right Expand ;

[0100] Substituting the above expansion results From this, we can obtain: ;

[0101] To address the impedance mismatch between the signal source and the load, both impedances must be adjusted simultaneously. For the signal source, its internal circuit parameters can be adjusted to change the output impedance; similarly, an impedance matching network can be used to transform the impedance of the load. Furthermore, impedance matching devices, such as directional couplers and power dividers, can be used to improve the impedance matching between the signal source and the load. In actual measurements, in addition to considering impedance mismatch, it is also important to keep the connectors clean and ensure good contact to avoid measurement errors caused by connector issues.

[0102] The third step is to optimize the power transfer equation based on the parameter definition information to obtain a more accurate and comprehensive power transfer analysis expression.

[0103] Substituting the parameter definitions into the power transfer equation, we can obtain the optimized power transfer analysis expression:

[0104]

[0105] Among them, molecules It can quantify the independent mismatch loss at both ends, denominator It can characterize the uncertainty gain related to phase.

[0106] Due to phase shift factor and double-ended coupling reflection coefficient The following relationship must be satisfied;

[0107]

[0108] in and These represent the phase angles of the signal source and the load reflection coefficient, respectively.

[0109] Substituting this into the power transfer equation yields a further optimized power transfer equation:

[0110]

[0111] The optimized power transfer equation is extended in logarithmic form:

[0112]

[0113] By using itemized quantization, the contribution of signal source mismatch, load mismatch, and phase coupling to the total error can be independently evaluated, which helps to more accurately locate problems in microwave sensing equipment.

[0114] The fourth step involves analyzing the impedance mismatch between the signal source and the load using power transfer analysis expressions and parameter definitions.

[0115] Based on power transfer ratio analysis: the power transfer ratio is obtained through measurement or calculation. Compare this to the ideal power transfer ratio (i.e., the power transfer ratio when the signal source and load are perfectly matched). ) compare, if If the value is significantly less than 1, it indicates an impedance mismatch problem.

[0116] Analysis based on reflection coefficient: According to the signal source reflection coefficient and load reflection coefficient The value is used to determine the matching degree between the signal source and the load. or near If the value is close to 0, it indicates a severe mismatch between the corresponding signal source or load and the transmission line; if it is close to 0, it indicates a good match.

[0117] Considering phase factor analysis: Observing the phase shift factor The impact on power transmission varies. The value causes the power transfer ratio to vary between its maximum and minimum values. By analyzing this variation, we can understand the specific impact of phase uncertainty on power transfer.

[0118] Based on the above analysis results, the mismatch between the signal source and the load impedance can be comprehensively evaluated. In this embodiment, corresponding improvement measures are taken according to the evaluation results, which can effectively optimize the performance and measurement accuracy of the equipment, and provide a reference for the debugging, maintenance and optimization of the equipment.

[0119] Finally, the microwave sensing device was adjusted based on the above-mentioned operational mismatch, and the adjusted microwave sensing device was obtained.

[0120] If a mismatch occurs between the signal source and the load impedance during the operation of a microwave sensing device, it will lead to an increase in reflected voltage and mismatch loss, thereby affecting the performance of the device. To solve this problem, this embodiment proposes an adjustment scheme for the microwave sensing device. The microwave sensing device is adjusted based on the following steps to finally obtain the adjusted device.

[0121] The first step is to combine The load impedance of the microwave sensing device is transformed to match the impedance of the transmission line by matching the network and the load impedance mismatch.

[0122] Combination To address the impedance mismatch between the matching network and the load, the load impedance of the microwave sensing device is transformed to match the transmission line impedance. Matching networks typically consist of inductors and capacitors. By appropriately selecting their parameters, impedance transformation can be achieved. For a given load impedance, the real part... and transmission line characteristic impedance Inductance can be calculated using the following formula. and capacitor Value:

[0123]

[0124] in, express Matching the inductance of the network, express The capacitance of the matching network, This represents the characteristic impedance of the transmission line. Indicates the angular frequency of the signal. This represents the real part of the load impedance.

[0125] In practical applications, the characteristic impedance of the transmission line should be consistent with the reference impedances of the signal source and the load; the real part of the load impedance should be real (for purely resistive loads) or dominated by the real part (for complex impedance scenarios, the imaginary part needs to be compensated). The formula is as follows: and The ratio adjusts the inductance value, when When (e.g., when the load impedance is low) Take a positive value; when In this case, matching needs to be achieved through a capacitor voltage divider network. It may be a negative value. and Sharing the same impedance ratio term ensures Network at target frequency Impedance transformation is achieved by forming a resonance.

[0126] If the load is adjustable, such as a variable resistor or variable capacitor, its impedance value can be adjusted to be close to that of a variable resistor or variable capacitor. For variable resistors, the resistance value can be changed by rotating the resistance adjustment knob; for variable capacitors, the capacitance value can be adjusted by changing the spacing or area of ​​the capacitor plates.

[0127] Impedance matching devices, such as directional couplers and power dividers, are inserted between the signal source and the load. A directional coupler couples a portion of the signal power to the load while simultaneously achieving impedance matching between the signal source and the load. A power divider distributes the input signal power evenly across multiple output ports, with the impedance of each output port matched to the transmission line impedance.

[0128] The second step involves adjusting the circuit parameters, impedance network, and phase offset of the microwave sensing device based on the mismatch between the signal source and the load impedance, and obtaining a characteristic impedance close to that of the transmission line, as well as an impedance network and a compensated offset factor that are adapted to it.

[0129] Internal circuit parameter adjustment: For the signal source section of the microwave sensing module, identify key parameters affecting the output impedance, such as transistor bias current, resistor and capacitor values, etc. By adjusting the internal circuit parameters, change the output impedance of the signal source to make it as close as possible to the characteristic impedance of the transmission line. .

[0130] Load impedance adjustment and impedance matching network design: Based on the actual impedance of the microwave sensing module load and the characteristic impedance of the transmission line, a corresponding impedance matching network is designed. The impedance network can be a single-section or multi-section matching network. In practical applications, the appropriate type can be selected according to the load characteristics and operating frequency. For loads with lower frequencies and lower bandwidth requirements, a single-section quarter-wavelength transmission line can be used for matching; for loads with higher frequencies and wider bandwidth requirements, a multi-section matching network can be used.

[0131] Phase offset factor measurement and compensation: In this embodiment, a vector network analyzer is used to measure the microwave sensing module to accurately obtain the phase angle of the signal source and load reflection coefficient. and Then, the phase offset factor is calculated.

[0132] Design a phase compensation circuit: Design a phase compensation circuit based on the phase shift factor. It can be implemented using components such as phase shifters and delay lines. For example, if a variable phase shifter is used, the phase shift amount can be changed by adjusting its control voltage, thereby compensating for the phase shift and maintaining a stable phase relationship of the signal during transmission.

[0133] The third step involves comprehensively adjusting the microwave sensing device based on load impedance, characteristic impedance, adaptive impedance network, and compensated offset factor, ultimately obtaining the adjusted microwave sensing device.

[0134] The technologies and components involved in the above adjustment strategies, such as impedance matching networks, variable load components, and impedance matching devices, are mature and reliable in the microwave field. Whether adjusting internal circuit parameters, using impedance transformation networks, or employing impedance matching devices, there are theoretical foundations and practical experience to refer to, providing technical support for the adjustment of microwave sensing equipment.

[0135] Phase offset factor measurement and compensation techniques are widely used in modern microwave measurement and communication systems. Phase information can be accurately measured using instruments such as vector network analyzers, and various phase control components such as phase shifters and delay lines possess high performance and reliability. Through proper design and integration of phase compensation circuits, the impact of phase uncertainty on power transmission can be effectively controlled. Furthermore, the aforementioned impedance matching networks and variable load components are relatively inexpensive and can be customized and selected according to actual needs.

[0136] In summary, adjusting the impedance of the microwave sensing device based on the signal source and load impedance mismatch can effectively improve the performance of the microwave sensing device, increase power transmission efficiency, reduce information measurement errors, and provide more reliable technical support for the application of microwave sensing devices.

[0137] S2. Deploy the adjusted microwave sensing equipment as described above, and use the adjusted microwave sensing equipment to monitor the power towers and collect information to obtain a power tower monitoring information database. The specific steps and implementation details are as follows:

[0138] The first step is to deploy and adjust the microwave sensing equipment based on the actual environmental conditions.

[0139] Investigate the actual environmental conditions of the power tower, survey the tower base and its surrounding environment, and record the topographic features in detail, including terrain undulation, slope, soil type, etc.; understand the distribution of surrounding vegetation, such as tree height and density; and analyze potential sources of interference in the surrounding area, such as high-voltage lines, large metal facilities, radio transmission towers, etc.

[0140] Before deployment, the adjusted microwave sensing equipment needs to be debugged, including signal transmission power calibration, receiver sensitivity testing, and antenna directivity adjustment, to ensure that the microwave sensing equipment can work normally under various environmental conditions.

[0141] Next, based on the environmental characteristics of the power tower base, the optimal installation location for the microwave sensing equipment is determined. A relatively open, unobstructed location with minimal interference around the power tower base can be selected to ensure that the microwave signal emitted by the equipment effectively covers the power tower base area and accurately receives reflected signals. During installation, the equipment installation instructions must be followed to ensure that the equipment is securely and horizontally installed. This prevents inaccurate monitoring data due to unstable installation. The impact of terrain on microwave signal propagation must also be considered, and the height and angle of the equipment should be adjusted accordingly to reduce signal obstruction and reflection interference.

[0142] After the equipment is installed, functional verification tests are conducted. By transmitting specific test signals, the equipment's ability to transmit and receive microwave signals normally is checked. The changes in parameters such as the phase and frequency of the reflected signals are observed to ensure they meet expectations. Any problems discovered during the verification process are promptly adjusted and repaired to further ensure that the equipment performance reaches its optimal state.

[0143] The second step is to select key monitoring locations for the power tower based on the actual environmental conditions.

[0144] The overall structure of the power tower is analyzed, including but not limited to the type of power tower (angle steel tower, steel pipe tower), height, tower body segmentation, crossarm structure, etc., to understand the stress characteristics and deformation laws of different components of the power tower under load, wind force and geological changes, and to identify the key parts of the power tower structure that are prone to settlement and deformation problems.

[0145] Based on historical geological disaster data and tower operation and maintenance records of the area where the power tower is located, further analysis is conducted on the location and causes of previous power tower subsidence, tilting and other accidents. Combined with the current actual operation status of the power tower and environmental conditions, high-risk areas that may have problems are predicted, and the relevant areas are considered as key monitoring locations.

[0146] Based on the actual site conditions and the overall structure of the power tower, the key monitoring locations of the power tower are determined. In this embodiment, these locations cover the power tower foundation, the connection between the tower body and the foundation, and key nodes of the tower body (the connection between the crossarm and the tower body, the location of the tower body slope change, etc.), ensuring effective monitoring of the overall structure of the power tower.

[0147] The third step is to set up information monitoring points during the power tower settlement monitoring process based on key monitoring locations.

[0148] A layout plan for information monitoring points is developed based on key monitoring locations. Considering factors such as the power tower's geometry, structural symmetry, and monitoring accuracy requirements, the number and density of monitoring points are rationally determined. In key areas of critical monitoring locations, the number of monitoring points is appropriately increased to improve the accuracy and reliability of the monitoring data. In an optional embodiment, multiple monitoring points are evenly distributed around the power tower at certain intervals to comprehensively monitor the tower's settlement.

[0149] Meanwhile, each information monitoring point is clearly marked to facilitate subsequent monitoring and maintenance. In this embodiment, the markings include the monitoring point number, location information, etc., and are made of durable materials to ensure clear visibility during long-term monitoring. Furthermore, detailed monitoring point files are established, recording the geographical location, coordinates, and surrounding environment of each monitoring point, providing foundational data for subsequent data analysis and processing.

[0150] Associate the information monitoring points with the deployed microwave sensing devices. Clearly define the microwave sensing device number and monitoring parameter settings for each monitoring point to ensure the devices can accurately collect relevant information from that point. In the power tower settlement monitoring and early warning system, establish a database mapping monitoring points to devices to facilitate data retrieval and management.

[0151] The fourth step involves monitoring and collecting information about the power tower based on the information monitoring points and the adjusted microwave sensing equipment, in order to obtain a power tower monitoring information database.

[0152] An information monitoring plan was developed based on the operating characteristics and monitoring needs of the power towers. This embodiment specifies parameters such as monitoring frequency and monitoring time periods. For power towers located in areas with complex geological conditions, the monitoring frequency can be appropriately increased to multiple monitoring sessions per day; for power towers with stable operation and favorable geological conditions, the monitoring frequency can be appropriately reduced to 3-4 monitoring sessions per week. Simultaneously, the data collection and transmission methods were determined to ensure that the data can be transmitted to the data processing center in a timely and accurate manner.

[0153] The adjusted microwave sensing equipment is activated according to the information monitoring plan to monitor the power tower in real time. The equipment continuously transmits microwave signals and receives reflected signals. Its built-in data processing module analyzes parameters such as phase and frequency of the reflected signals to extract information related to tower settlement and micro-motion. The collected monitoring data is transmitted to the data processing center in real time to ensure its timeliness and integrity. Encryption technology is used during data transmission to ensure data security and prevent data leakage and tampering.

[0154] After receiving the monitoring data, the data processing center of the power tower settlement monitoring and early warning system performs preprocessing work on it, including but not limited to data cleaning, noise reduction, and normalization, in order to improve the quality of the monitoring data.

[0155] The processed and analyzed monitoring data will be stored according to specific formats and standards to establish a power tower monitoring information database. The database should have a robust data structure, enabling convenient storage, retrieval, and management of various monitoring data, primarily including monitoring time, monitoring point location, monitoring parameter values, and data analysis results. Simultaneously, the database should be equipped with corresponding data retrieval and statistical analysis functions to facilitate users' rapid access to the necessary monitoring information and provide decision support for the operation, maintenance, and management of power towers.

[0156] Through the above implementation steps, we can ensure the effective deployment and application of the adjusted microwave sensing equipment in power tower monitoring, build a comprehensive and accurate power tower monitoring information database, and provide a data foundation and information reference for power tower settlement monitoring and safety early warning.

[0157] S3. Extract the baseband signal set of the power tower monitoring points from the aforementioned power tower monitoring information database. Based on the baseband signal set, obtain the distance-angle dimension parameter information of the power tower monitoring points. Analyze the total displacement prediction result of the power tower based on the distance-angle dimension parameter information and the baseband signal set. The specific implementation details are as follows:

[0158] First, the baseband signal set of the power tower monitoring points is extracted from the aforementioned power tower monitoring information database.

[0159] The first step is to obtain channel information, signal amplitude, phase information, and frequency data for a single information monitoring point based on the power tower monitoring information database.

[0160] Based on the implementation details, it is known that a total of [number] monitoring stations were set up during the power tower settlement monitoring process. The target monitoring points, including the key nodes, cover the tower foundation, the connection between the tower body and the foundation, and key nodes of the tower body, to ensure effective monitoring of the overall structural safety of the power tower.

[0161] At the same time, each target monitoring point is configured with There should be multiple information transmission channels. The selection of these channels should take into account factors such as transmission stability and anti-interference capabilities to ensure accurate and timely transmission of monitoring data.

[0162] The sweep frequency center frequency is set according to the power tower monitoring information database. Using the formula Wavelength parameters can be calculated ,in Represents the speed of light Wavelength parameters play a crucial role in subsequent phase analysis and displacement calculations; therefore, it is essential to ensure the center frequency of the sweep frequency. The measurement accuracy.

[0163] A reference phase is introduced to eliminate system drift. and definition ,in This indicates the reference channel phase. Phase reference calibration can effectively eliminate phase errors caused by factors such as system clock drift and temperature changes, thereby improving the accuracy of monitoring data.

[0164] And determine the baseband signal amplitude generated by the information transmission channel corresponding to different information monitoring points. Beat frequency Modulation phase related to vibration displacement and additive white Gaussian noise term The above parameters will be used in the subsequent baseband signal analysis and modeling process.

[0165] The phase difference method is used to calculate the phase change of the reflected signal. By comparing the phase difference of the reflected signal at different times, some systematic errors can be effectively eliminated and the accuracy of phase measurement can be improved.

[0166] Frequency offset can be determined by using spectrum analysis. Spectrum analysis can convert a signal from the time domain to the frequency domain and accurately obtain the frequency offset by analyzing the peak positions and frequency distribution in the spectrum.

[0167] The second step involves analyzing the baseband signal of a single monitoring point based on channel information, signal amplitude, phase information, and frequency data.

[0168] Based on the target data set and microwave vibration measurement method, the vibration of the target is inverted using interferometric phase modulation information. The displacement changes of the monitoring points in the radar line-of-sight direction at adjacent time points satisfy the following relationship:

[0169]

[0170] in, This represents the change in displacement of the target along the radar line of sight at adjacent time points. This indicates the wavelength corresponding to the center frequency of the sweep frequency. Represents pi (π). This represents the change in interference phase between adjacent moments. Represents a time variable.

[0171] However, the above formula only has one-dimensional distance resolution capability. When different target monitoring points are in close or the same distance unit, two components with similar beat frequencies are easily coupled or even overlapped, making it difficult to accurately distinguish between different monitoring points. Severe coupling interference occurs between the target components, which significantly increases the measurement error and may even cause serious distortion of the displacement measurement waveform.

[0172] To address the aforementioned issues, this embodiment employs a combined distance and angle approach to effectively identify, locate, and extract information on power tower displacement. By considering both distance and angle information from different monitoring points, it effectively enhances the resolution of monitoring points, suppresses coupling interference, and improves the accuracy and reliability of monitoring data and analysis results.

[0173] Based on the target data set of the microwave sensing module, an assessment of a single monitoring point under the frequency sweep cycle was established. A baseband signal analysis model for a single information transmission channel is established. Based on this model, the baseband signal of a single information monitoring point is analyzed, and the following relationship is satisfied:

[0174]

[0175] in, This represents the baseband signal output by different information transmission channels for a single target monitoring point. Indicates the information transmission channel number. This indicates the number of information transmission channels during the power tower monitoring process. Indicates the first The baseband signal amplitude generated by each information transmission channel Represents the imaginary unit. Represents pi (π). Indicates the first The beat frequency generated by each information transmission channel Indicates the first The modulation phase related to the vibration displacement of the information transmission channel. This represents the additive white Gaussian noise term.

[0176] The third step involves integrating and analyzing the baseband signals from individual information monitoring points to construct information, thereby obtaining a set of baseband signals from the power tower monitoring points.

[0177] By combining the baseband signals from all monitoring points, a monitoring system for power tower settlement can be constructed. The set of baseband signals from each target monitoring point is represented in matrix form in this embodiment:

[0178]

[0179] in, Represents the global baseband signal matrix. This matrix represents the discrete time series of baseband signals from different information transmission channels. It has a clear structure, with each row corresponding to a channel and each column corresponding to a monitoring point. The elements are discrete sampled signals, which facilitates subsequent monitoring data processing and extraction analysis.

[0180] Furthermore, the global baseband signal matrix undergoes data verification and evaluation, checking the completeness, accuracy, and consistency of the data to ensure there are no missing data or outliers. A comparative analysis is then performed with actual monitoring data to assess the reliability and effectiveness of the baseband signals. If any problems are found, the process is immediately repeated to troubleshoot and correct them, ensuring the accuracy and reliability of the final baseband signal set from the power tower monitoring points. These steps enable the accurate extraction of the baseband signal set from the power tower monitoring information database, providing data support for power tower settlement monitoring and structural safety assessment.

[0181] Then, after extracting the baseband signal set of the power tower monitoring points, the distance-angle dimension parameter information of the power tower monitoring points is further obtained.

[0182] The first step is to perform a two-dimensional Fourier transform on the baseband signal set to obtain distance-dimensional transform information and angle-dimensional transform information.

[0183] The baseband signal matrix is ​​known to satisfy the following relationship:

[0184]

[0185] in Each row of the matrix corresponds to a channel, and each column corresponds to a monitoring point. The elements are discrete sampled signals. By performing a two-dimensional Fourier transform on the matrix, distance and angle transformation information can be obtained, thereby enabling joint analysis of distance and angle at different monitoring points and providing a foundation for subsequent analysis of power tower settlement displacement and key parameters.

[0186] In this embodiment, a two-dimensional Fast Fourier Transform (FFT) is used to transform the baseband signal matrix. The two-dimensional FFT algorithm is computationally efficient and simple to implement. It can quickly convert signals from the time-space domain to the frequency-angle domain, thereby obtaining joint analysis of distance-angle dimensions.

[0187] Distance-dimensional FFT: along the baseband signal matrix The row direction (channel m) is used for Point FFT, where the distance dimension FFT resolution ,in, Represents the speed of light. This represents the sweep bandwidth, which should be selected appropriately based on actual monitoring requirements and system performance when performing distance-dimensional FFT. The value is set to ensure sufficient distance resolution.

[0188] Angular-dimensional FFT: along the baseband signal matrix Column direction (number of monitoring points n) Point FFT, where the angle dimension FFT resolution ,in Indicates wavelength. Indicates the aperture of the antenna array, also The value should be reasonably determined based on the monitoring scenario and angular resolution requirements.

[0189] Through the aforementioned two-dimensional FFT processing, a joint dimensional analysis of distance and angle can be performed. Based on signal model analysis, it is known that the vibration displacement of the power tower can be tracked and obtained through nonlinear demodulation and interference phase analysis based on the joint distance-angle dimension. During the joint dimensional analysis, the signal phases at different distances and angles contain information about the power tower's vibration displacement. By performing nonlinear demodulation processing on these phases, the vibration displacement of the power tower at different locations can be extracted.

[0190] The second step is to obtain the distance-dimensional phase rotation factor based on the distance-dimensional transformation information.

[0191] The distance-dimensional phase rotation factor is mainly used to describe the rotation characteristics of the signal phase in the distance dimension. It reflects the phase change of the signal at different distances. By introducing the distance-dimensional phase rotation factor, the phase of the signal in the distance dimension can be corrected and adjusted, so as to analyze the distance-related parameter information more accurately.

[0192] The distance-dimensional phase rotation factor is as follows:

[0193]

[0194] in, Represents the imaginary unit. Indicates frequency index, Indicates the distance dimension FFT resolution. This represents the number of points at a distance from the FFT dimension. This represents the distance dimension correction coefficient. During the calculation process, the accuracy of each parameter must be ensured to guarantee the effectiveness of the phase rotation factor.

[0195] The third step is to obtain the angular phase rotation factor based on the angular dimension transformation information.

[0196] The angular phase rotation factor can describe the rotation characteristics of the signal phase in the angular dimension, reflecting the phase change of the signal at different angles. Introducing the angular phase rotation factor can perform phase correction and adjustment on the signal in the angular dimension, which helps to analyze angle-related parameter information more accurately.

[0197] The angular phase rotation factors mentioned above are as follows:

[0198]

[0199] in, Represents the imaginary unit. Indicates angle index, Represents the angular dimension FFT resolution. This represents the number of points in the angular dimension of the FFT. This represents the angular dimension correction coefficient.

[0200] The fourth step is to obtain the distance-angle dimension parameter information of the power tower monitoring point based on the distance dimension transformation information, angle dimension transformation information, distance dimension phase rotation factor, and angle dimension phase rotation factor.

[0201] The distance-dimensional transformation information, angle-dimensional transformation information, distance-dimensional phase rotation factor, and angle-dimensional phase rotation factor are comprehensively analyzed. The distance-dimensional transformation information and angle-dimensional transformation information provide the frequency distribution characteristics of the signal in terms of distance and angle, while the distance-dimensional and angle-dimensional phase rotation factors are used to correct and adjust the signal phase.

[0202] By comprehensively processing the above information, the distance-angle dimension parameters of the power tower monitoring point can be obtained. These parameters include, but are not limited to, the vibration displacement, phase change, and frequency shift of the power tower at different distances and angles.

[0203] The above steps enable accurate acquisition of distance-angle dimension parameters of power tower monitoring points based on baseband signal sets, providing data support for effective monitoring of power tower settlement and structural safety assessment.

[0204] Finally, the total displacement prediction results of the power tower are analyzed based on the distance-angle dimension parameter information and the baseband signal set.

[0205] The first step is to establish a phase analysis formula for monitoring points within a fixed period based on distance-angle dimension parameter information.

[0206] By analyzing the phase of monitoring points within a fixed period, the phase information of the target in the joint range-angle domain is extracted. This information can reflect the vibration displacement of the target and provide key data for subsequent displacement prediction.

[0207] For different information monitoring points during the power tower settlement monitoring process, the phase calculation formula over t frequency sweep cycles is as follows:

[0208]

[0209] in, Indicates the first Information monitoring points at Phase of each sweep cycle, This indicates the operation of taking the phase of a complex number. This indicates the number of target monitoring points during the power tower settlement monitoring process. This indicates the number of information transmission channels during the power tower monitoring process. Indicates the number of the target monitoring point. A number indicating the number of information transmission channels. express The first sweep frequency cycle The first channel One sampled signal, The phase rotation factor represents the distance dimension. The phase rotation factor represents the angular dimension. This represents the number of points in the distance dimension. The number of points representing the angular dimension. Represents the distance dimension correction coefficient. This represents the angular dimension correction coefficient.

[0210] Complex phase operations can be used to demodulate the phase information of the monitoring point in the distance-angle joint domain using a two-dimensional FFT. Specifically, a two-dimensional FFT is first performed on the baseband signal set to transform the signal from the time-space domain to the frequency-angle domain. Then, the phase information at the corresponding position is extracted from the transformed result. This phase information reflects the vibration and displacement characteristics of the monitoring point.

[0211] The second step involves analyzing the phase analysis results of different information monitoring points within a fixed sweep frequency period using phase analysis of monitoring points within a fixed period.

[0212] For all information monitoring points within a fixed frequency sweep period, their phase values ​​are calculated separately to gain a comprehensive understanding of the phase changes at different information monitoring points.

[0213] The phase values ​​of each monitoring point within a fixed frequency sweep cycle are recorded and organized. A curve showing the phase change over time or monitoring point location can also be plotted. By observing the trend of the curve, the fluctuation pattern and trend of phase change, as well as the phase differences between different monitoring points, can be analyzed. If the phase change trends of some monitoring points are similar, it may indicate that the targets at the related monitoring point locations are affected by the same factors; while monitoring points with large phase differences may have different vibration sources or vibration characteristics.

[0214] The third step involves combining the information from monitoring points and phase analysis results during the power tower settlement monitoring process to construct a displacement prediction function for the monitoring points, thereby providing technical support for the prediction of the total displacement of the power tower.

[0215] Line of sight displacement at different target monitoring points It can be represented as:

[0216]

[0217] in, This indicates the displacement of the line of sight direction at different target monitoring points. Indicates the first The effective wavelength of each target monitoring point Indicates the first Each target monitoring point is at Phase of each sweep cycle, Indicates the moving average phase. This represents the confidence level correction factor.

[0218] The moving average phase is calculated by averaging the phase values ​​within a certain time window, and can be used to eliminate random errors and noise interference in phase measurement. The confidence correction factor needs to be set according to the actual monitoring environment and data reliability, and its value ranges from 0 to 1. It is mainly used to adjust the confidence of the displacement prediction results.

[0219] The fourth step involves obtaining displacement analysis results for monitoring points with different information by using the monitoring point displacement prediction function and the baseband signal set.

[0220] The displacement prediction function of the monitoring point and relevant data (phase value, effective wavelength, etc.) in the baseband signal set are input into the displacement prediction model. According to the displacement prediction function of the monitoring point, the line-of-sight displacement of each information monitoring point is calculated in sequence. The calculated displacement results are recorded, including but not limited to the monitoring point number, displacement value, calculation time, etc., for subsequent analysis and query. Based on this, the displacement analysis results of different information monitoring points are obtained.

[0221] The fifth step is to integrate the displacement analysis results from different information monitoring points to analyze the displacement of the power tower and obtain the total displacement prediction result of the power tower.

[0222] By integrating the displacement analysis results of different information monitoring points and taking into account the location distribution and importance of each monitoring point, this embodiment uses a weighted average method to calculate the total displacement of the power tower. The weighted average method can determine the weight coefficients based on factors such as the distance between the monitoring point and the key parts of the power tower and the degree of influence of the monitoring point on the structural safety of the power tower, so that the total displacement prediction result can better reflect the actual displacement of the power tower.

[0223] Finally, the characteristic parameter information of the power tower, the displacement analysis results of different monitoring points, and the total displacement prediction results are digitized according to a preset encoding rule to generate a digital signal that accurately reflects the micro-motion changes of the power tower base. In this embodiment, the encoding rule needs to be designed according to actual needs to ensure that the digital signal can accurately and uniquely represent the characteristics of the micro-motion changes. A binary encoding method can be used, determining the number of bits according to the value range of the characteristic parameter, mapping each characteristic parameter to a unique binary code group. At the same time, to facilitate subsequent data processing and analysis, necessary identification information, such as monitoring time and monitoring point number, can be added to the digital signal.

[0224] After converting the characteristic parameters into digital signals according to the encoding rules, the digital signals are stored and managed. A suitable storage medium (database, file system) can be selected to establish a complete data storage structure for subsequent querying, analysis and application, providing strong support for the real-time monitoring and safe operation of power towers.

[0225] S4. To achieve accurate control and timely early warning of power tower settlement, a settlement monitoring and early warning mechanism has been established. This mechanism, along with the total displacement prediction results and the power tower monitoring database, needs to be combined to conduct a comparative analysis of the power tower settlement situation. The specific implementation steps are as follows:

[0226] The first step is to set a settlement benchmark threshold and a graded assessment mechanism in the settlement monitoring and early warning mechanism.

[0227] The settlement benchmark threshold needs to be determined by comprehensively considering various factors such as tower design requirements, geological conditions, and historical monitoring data. This can help determine the safe settlement threshold for the tower base. The settlement tolerance value in the tower design specification (such as referring to GB50010-2010 Code for Design of Concrete Structures), the soil compression modulus provided in the geological exploration report, and other key information such as the average settlement rate over the past 5 years can be used as references. Furthermore, the initial threshold can be calculated using a weighted average method to ensure the scientific and reasonable setting of the threshold.

[0228] This embodiment constructs a multi-level hierarchical assessment mechanism, dividing safety thresholds into different levels to correspond to different degrees of settlement risk. This hierarchical assessment mechanism includes a warning threshold level, an alarm threshold level, and a limit threshold level, as detailed below:

[0229] Warning threshold level: set at 50% of the settlement baseline threshold. When the value of the micro-motion change digital signal exceeds this threshold, the system will automatically issue a yellow warning signal.

[0230] Alarm threshold level: set to 70% of the settlement baseline threshold. If the signal value exceeds this threshold, the system will issue an orange alarm signal.

[0231] Limit threshold level: set to 100% of the settlement baseline threshold. Once the signal value reaches or exceeds this threshold, the system triggers a red emergency power-off operation.

[0232] Meanwhile, considering the impact of seasonal geological changes on the settlement benchmark threshold, the LSTM time series model is used to automatically optimize the size of the settlement benchmark threshold every quarter based on newly collected data, so that the threshold can dynamically adapt to changes in actual geological conditions.

[0233] In addition, threshold data recording and management are required. The set safety thresholds should be accurately stored in the system storage unit for later retrieval and retrieval. During monitoring, the digital signal values ​​corresponding to the micro-movements of the power tower base should be recorded in real time, along with detailed records of the time and extent of each threshold exceedance, providing complete data support for subsequent analysis and tracing. A structured database table should be established, mainly containing the following key fields: monitoring point ID, timestamp, settlement amount, trigger threshold level, processing status, and coordinate information.

[0234] The second step involves a dynamic comparative analysis of the displacement analysis results and total displacement prediction results at different information monitoring points based on the settlement benchmark threshold and the graded evaluation mechanism, in order to obtain the settlement analysis results of the power tower.

[0235] First, a line-of-sight displacement comparison is performed. The line-of-sight displacement of different information monitoring points is compared and analyzed with the benchmark threshold one by one. This can help to promptly identify potential safety hazards in the power tower area corresponding to different information monitoring points.

[0236] Then, real-time data analysis is performed. The system's data processing unit continuously and in real-time analyzes the micro-motion data after digital conversion and compares it with the stored safety threshold, thereby grasping the actual situation of the power tower base settlement in real time.

[0237] Simultaneously, multi-dimensional comparative analysis is conducted. Spatial dimension analysis: By comparing the settlement differences at different monitoring points of the same power tower, and analyzing the inconsistency of settlement at each monitoring point, non-uniform settlement risks are accurately identified, providing a basis for subsequent maintenance and treatment. Temporal dimension analysis: The trend of settlement rate changes is analyzed, and data analysis methods are used to predict the settlement and changes in the area where the power tower is located in the next 48-72 hours, which is conducive to making preparations for subsequent responses. Environmental dimension analysis: Combining environmental data such as temperature, humidity, and rainfall in the area where the power tower is located, the settlement monitoring results of the power tower are comprehensively analyzed to eliminate the interference of environmental factors on the settlement situation and ensure the accuracy of the power tower settlement prediction results.

[0238] The third step involves combining the safety early warning devices in the settlement monitoring and early warning mechanism, the results of power tower settlement analysis, and the power tower monitoring information database to release safety early warning information about power tower settlement.

[0239] The information fed back by the safety early warning device in the settlement monitoring and early warning mechanism, the results of power tower settlement analysis, and relevant data in the power tower monitoring information database are comprehensively integrated to further ensure the integrity and accuracy of the information.

[0240] Based on the integrated information and in accordance with the established hierarchical assessment mechanism, the system platform promptly and accurately releases safety warning information on power tower settlement. In this embodiment, the warning information includes, but is not limited to, key information such as the location of the power tower, the settlement situation, the trigger threshold level, and corresponding handling suggestions, so that relevant personnel can quickly understand the situation and take effective measures.

[0241] The fourth step is to achieve real-time monitoring and intelligent early warning of power tower settlement based on safety warning information.

[0242] Utilizing monitoring equipment and technologies, the system continuously monitors the settlement of power towers in real time, ensuring timely capture of any changes and data related to settlement. Based on real-time monitoring data and a pre-set hierarchical assessment mechanism, the system automatically performs intelligent analysis and judgment. Once settlement is detected to reach or exceed the corresponding threshold, an appropriate early warning signal is immediately triggered, and the warning information is promptly pushed to relevant personnel, achieving an intelligent early warning function for power tower settlement. Simultaneously, the system should have the function of automatically recording and storing early warning information for subsequent querying and statistical analysis.

[0243] By implementing the above steps, a complete, scientific, and feasible monitoring and early warning mechanism for power tower settlement can be established, enabling real-time monitoring and intelligent early warning of power tower settlement, and effectively ensuring the safe operation and stable functioning of power towers.

[0244] Please see Figure 2 In an optional embodiment, to efficiently execute the microwave-sensing-based power tower settlement monitoring and early warning method provided by this invention, the present invention also provides a microwave-sensing-based power tower settlement monitoring and early warning system. The system includes a processor, an input device, an output device, and a memory, which are interconnected. The memory stores a computer program, which includes program instructions. The processor is configured to call the program instructions to execute the specific steps of the microwave-sensing-based power tower settlement monitoring and early warning method and related embodiments provided by this invention. The microwave-sensing-based power tower settlement monitoring and early warning system of this invention has a complete structure and is objectively stable.

[0245] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered within the scope of the claims and specification of the present invention.

Claims

1. A method for monitoring and early warning of power tower settlement based on microwave sensing, characterized in that, The method includes: Analyze the operational mismatch of the microwave sensing device, adjust the microwave sensing device according to the operational mismatch, and obtain the adjusted microwave sensing device. The analysis of operational mismatches in microwave sensing equipment includes: The incident power and reflected power of the signal are analyzed based on the configuration information of the microwave sensing device, and the actual load power of the microwave sensing device is obtained based on the incident power and the reflected power. Based on the actual power of the load, a mismatch loss calculation formula is constructed to obtain the mismatch loss result of the microwave sensing device. Based on the mismatch loss result, the load impedance mismatch of the microwave sensing device is analyzed. The adjusted microwave sensing device is deployed to monitor and collect information about the power towers in order to obtain a power tower monitoring information database. Extract the baseband signal set of the power tower monitoring points from the power tower monitoring information database, obtain the distance-angle dimension parameter information of the power tower monitoring points based on the baseband signal set, and analyze the total displacement prediction result of the power tower based on the distance-angle dimension parameter information and the baseband signal set. A settlement monitoring and early warning mechanism is constructed, and the settlement situation of the power tower is compared and analyzed by combining the settlement monitoring and early warning mechanism, the total displacement prediction results and the power tower monitoring information database, so as to realize real-time monitoring and intelligent early warning of power tower settlement. The analysis of the total displacement prediction result of the power tower based on the distance-angle dimension parameter information and the baseband signal set includes: A phase analysis formula for monitoring points within a fixed period is established based on the distance-angle dimension parameter information. The phase analysis results of different information monitoring points within the fixed sweep frequency period are analyzed by phase analysis of the monitoring points within the fixed period. A displacement prediction function for monitoring points is constructed by combining the information monitoring points during the power tower settlement monitoring process with the phase analysis results. Displacement analysis results for monitoring points with different information are obtained by using the monitoring point displacement prediction function and the baseband signal set. The displacement analysis results from the different information monitoring points are integrated to analyze the displacement of the power tower and obtain the total displacement prediction result of the power tower. The phase calculation formula for different information monitoring points during the power tower settlement monitoring process over t frequency sweep cycles is as follows: ， in, Indicates the first Each target information monitoring point is at Phase of each sweep cycle, This indicates the operation of taking the phase of a complex number. This indicates the number of target monitoring points during the power tower settlement monitoring process. Indicates the number of receive channels. express The first sweep frequency cycle The first channel One sampled signal, The phase rotation factor represents the distance dimension. Represents the imaginary unit. Represents pi (π). Indicates frequency index, Indicates the distance dimension FFT resolution. The phase rotation factor represents the angular dimension. Indicates angle index, Represents the angular dimension FFT resolution. This represents the number of points in the distance dimension. The number of points representing the angular dimension. Represents the distance dimension correction coefficient. Indicates the angular dimension correction coefficient; Line of sight displacement at different target monitoring points It can be represented as: ， in, This indicates the displacement of the line of sight direction at different target monitoring points. Indicates the first The effective wavelength of each target monitoring point Represents pi (π). Indicates the first Each target monitoring point is at Phase of each sweep cycle, Indicates the moving average phase. This represents the confidence level correction factor.

2. The method for monitoring and early warning of power tower settlement based on microwave sensing according to claim 1, characterized in that, The analysis of operational mismatches in microwave sensing equipment includes: The signal source and load parameters of the microwave sensing device are standardized and defined, and the parameter definition information is obtained. A power transfer equation is established based on the microwave signal reflection of the microwave sensing device; The power transfer equation is optimized based on the parameter definition information to obtain a power transfer analysis expression; The mismatch between the signal source and load impedance is analyzed using the power transfer analysis expression and the parameter definition information.

3. The method for monitoring and early warning of power tower settlement based on microwave sensing according to claim 2, characterized in that, The step of adjusting the microwave sensing device based on the operational mismatch and obtaining the adjusted microwave sensing device includes: Combination The matching network and the load impedance mismatch condition transform the load impedance of the microwave sensing device to obtain a load impedance that matches the transmission line impedance. The circuit parameters, impedance network, and phase offset of the microwave sensing device are adjusted according to the mismatch between the signal source and the load impedance, and the characteristic impedance, the adapted impedance network, and the compensated offset factor close to the transmission line are obtained. The adjusted microwave sensing device is obtained based on the load impedance, the characteristic impedance, the adaptive impedance network, and the compensated offset factor.

4. The method for monitoring and early warning of power tower settlement based on microwave sensing according to claim 1, characterized in that, The deployment of the adjusted microwave sensing device, and the monitoring and information collection of the power tower through the adjusted microwave sensing device to obtain a power tower monitoring information database, includes: Deploy the adjusted microwave sensing equipment based on the actual environmental conditions; Select key monitoring locations for the power tower based on the actual environmental conditions; Information monitoring points are set up during the power tower settlement monitoring process based on the aforementioned key monitoring locations; The power tower is monitored and information is collected based on the information monitoring points and the adjusted microwave sensing equipment to obtain a power tower monitoring information database.

5. The method for monitoring and early warning of power tower settlement based on microwave sensing according to claim 1, characterized in that, The set of baseband signals from power tower monitoring points extracted from the power tower monitoring information database includes: Based on the aforementioned power tower monitoring information database, channel information, signal amplitude, phase information, and frequency data of a single information monitoring point are obtained; Analyze the baseband signal of a single information monitoring point based on the channel information, the signal amplitude, the phase information, and the frequency data; The baseband signals of the individual information monitoring points are integrated, analyzed, and information is constructed to obtain the baseband signal set of the power tower monitoring points.

6. The method for monitoring and early warning of power tower settlement based on microwave sensing according to claim 1, characterized in that, The distance-angle dimension parameter information of the power tower monitoring point obtained based on the baseband signal set includes: A two-dimensional Fourier transform is performed on the baseband signal set to obtain distance-dimensional transform information and angle-dimensional transform information; The distance-dimensional phase rotation factor is obtained based on the distance-dimensional transformation information. The angular phase rotation factor is obtained based on the angular transformation information. The distance-angle dimension parameter information of the power tower monitoring point is obtained based on the distance dimension transformation information, the angle dimension transformation information, the distance dimension phase rotation factor, and the angle dimension phase rotation factor.

7. The method for monitoring and early warning of power tower settlement based on microwave sensing according to claim 1, characterized in that, The aforementioned construction of a settlement monitoring and early warning mechanism, combined with the settlement monitoring and early warning mechanism, the total displacement prediction results, and the power tower monitoring information database, involves comparative analysis of the power tower settlement situation to achieve real-time monitoring and intelligent early warning of power tower settlement, including: The settlement monitoring and early warning mechanism includes a settlement benchmark threshold and a graded assessment mechanism. Based on the settlement benchmark threshold and the graded evaluation mechanism, the displacement analysis results of different information monitoring points and the total displacement prediction results are dynamically compared and analyzed to obtain the power tower settlement analysis results. By combining the safety early warning device in the settlement monitoring and early warning mechanism, the settlement analysis results of the power tower, and the power tower monitoring information database, safety early warning information on power tower settlement is released. Real-time monitoring and intelligent early warning of power tower settlement are achieved based on the aforementioned safety warning information.

8. A power tower settlement monitoring and early warning system based on microwave sensing, characterized in that, The system includes a processor, an input device, an output device, and a memory, which are interconnected. The memory is used to store a computer program, which includes program instructions. The processor is configured to call the program instructions to execute the microwave sensing-based power tower settlement monitoring and early warning method as described in any one of claims 1-7.

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