Electric tower settlement monitoring and early warning method and system based on microwave sensing

Abstract

The invention relates to the technical field of electric power facility monitoring, in particular to an electric tower settlement monitoring and early warning method and system based on microwave sensing, and the method comprises the steps: analyzing the operation mismatching condition of microwave sensing equipment, and adjusting the microwave sensing equipment to obtain the adjusted microwave sensing equipment; performing monitoring and information acquisition on the electric tower through the adjusted microwave sensing equipment to obtain an electric tower monitoring information base; extracting a baseband signal set of the electric tower monitoring points from the electric tower monitoring information base, obtaining distance-angle dimension parameter information of the electric tower monitoring points, and analyzing a total displacement prediction result of the electric tower according to the distance-angle dimension parameter information and the signal set; and comparing and analyzing the settlement condition of the electric tower by combining a settlement monitoring and early warning mechanism, the total displacement prediction result and an information base to obtain an electric tower settlement analysis result. The displacement condition of the electric tower is predicted and analyzed based on microwave sensing information, and real-time monitoring and intelligent early warning of the settlement condition of the electric tower are achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power facility monitoring, in particular to a microwave perception-based electric tower settlement monitoring and early warning method and system. BACKGROUND

[0002] In the process of power transmission, electric towers are prone to settlement problems due to various factors. Uncontrollable factors such as landslides and geological disasters can directly damage the geological structure of the area where the electric tower is located, thereby causing the electric tower to settle. Dynamic changes in underground water, such as water level fluctuations and water erosion, can change the geological conditions, ultimately leading to settlement of the electric tower. Once the electric tower settles, it will pose a serious safety hazard to the operation of the power grid and cause many inconveniences and losses to social production and life.

[0003] Traditional electric tower inspection methods have significant limitations. First, it is difficult to achieve comprehensive coverage for remote areas using traditional electric tower inspection methods, and it is difficult to detect electric tower settlement in a timely manner. Second, traditional monitoring methods mainly rely on inspection experience and regular checks, and are difficult to capture the instantaneous settlement risks of electric towers in real time, and are unable to take timely measures in the early stages of settlement.

[0004] In addition, tower settlement is influenced by many factors such as geological conditions, climate, construction technology, etc., and its development law is complex and variable, with uncertainty and concealment. Traditional data monitoring methods have low information monitoring accuracy, delayed data transmission, and inaccurate monitoring results, and are unable to achieve digital management of electric tower detection information, making it difficult to achieve real-time monitoring and timely warning of electric tower settlement.

[0005] Therefore, a method is needed to accurately monitor the micro-motion changes of electric towers and obtain effective information, achieve digital transmission and effective management of electric tower monitoring information, and intelligently monitor and accurately predict electric tower settlement, thereby identifying tower foundation settlement risks and providing safety warnings, further ensuring the safe and stable operation of the power grid. SUMMARY

[0006] In view of the deficiencies of the existing method and the needs of practical application, in order to effectively monitor the micro-motion change of the electric tower and obtain relevant information, the related algorithm is used to analyze and predict the electric tower situation and the settlement state, so as to realize the accurate identification and timely warning of the electric tower settlement risk, and further guarantee the safe and stable operation of the power grid. On the one hand, the present application provides an electric tower settlement monitoring and warning method based on microwave perception, which comprises the following steps: analyzing the operation mismatching condition of the microwave perception device, adjusting the microwave perception device according to the operation mismatching condition, and obtaining the adjusted microwave perception device; deploying the adjusted microwave perception device, monitoring and information collecting the electric tower by the adjusted microwave perception device to obtain an electric tower monitoring information database; extracting a baseband signal set of the electric tower monitoring point from the electric tower monitoring information database, obtaining distance-angle dimension parameter information of the electric tower monitoring point based on the baseband signal set, analyzing the total displacement prediction result of the electric tower according to the distance-angle dimension parameter information and the baseband signal set; constructing a settlement monitoring and warning mechanism, combining the settlement monitoring and warning mechanism, the total displacement prediction result and the electric tower monitoring information database to compare and analyze the electric tower settlement situation, so as to realize the real-time monitoring and intelligent warning of the electric tower settlement.

[0007] The microwave perception device is adjusted in the present application, which can make the device better adapt to the actual environment and working requirements of electric tower monitoring, help to improve the accuracy and reliability of data acquisition, and provide basic data for subsequent electric tower state analysis; the total displacement prediction result of the electric tower is analyzed according to the multi-dimensional parameter information and signal processing algorithm, which can more accurately predict the displacement trend of the electric tower, and help to discover the potential settlement problem of the electric tower in advance.

[0008] Optionally, the analysis of the operation mismatching condition of the microwave perception device comprises: analyzing the incident power and the reflected power of the signal according to the composition information of the microwave perception device; obtaining the actual load power of the microwave perception device based on the incident power and the reflected power; constructing a mismatch loss calculation formula according to the actual load power; obtaining the mismatch loss result of the microwave perception device through the mismatch loss calculation formula; and analyzing the load impedance mismatching condition of the microwave perception device based on the mismatch loss result.

[0009] The actual load power is obtained by the incident power and the reflected power of the signal in the present application, which can clearly understand the power consumption of the microwave perception device under different working conditions, further adjust the device, and ensure the stable operation of the device under the best power, so as to improve the operation efficiency of the device.

[0010] Optionally, the operation mismatch condition of the microwave sensing device is analyzed, including: defining the signal source and load parameters of the microwave sensing device, and obtaining parameter definition information; establishing a power transmission equation according to the microwave signal reflection condition of the microwave sensing device; optimizing the power transmission equation based on the parameter definition information to obtain a power transmission analysis expression; and analyzing the mismatch condition between the signal source and the load impedance by using the power transmission analysis expression and the parameter definition information.

[0011] The present application can reduce signal reflection in the transmission process, reduce signal distortion and interference, and thus ensure stable signal transmission by adjusting the signal source and load impedance to keep the device in good condition.

[0012] Optionally, the microwave sensing device is adjusted according to the operation mismatch condition, and the adjusted microwave sensing device is obtained, including: combining The load impedance of the microwave sensing device is transformed according to the mismatch condition of the matching network and the load impedance, and the load impedance matched with the transmission line impedance is obtained; 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, and the characteristic impedance close to the transmission line, the adaptive impedance network and the compensated offset factor are obtained; and the adjusted microwave sensing device is obtained based on the load impedance, the characteristic impedance, the adaptive impedance network and the compensated offset factor.

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

[0014] Optionally, the adjusted microwave sensing device is deployed, and the power tower is monitored and information is collected by using the adjusted microwave sensing device to obtain a power tower monitoring information database, including: deploying the adjusted microwave sensing device based on the actual environment; selecting a key monitoring position of the power tower in combination with the actual environment; setting an information monitoring point in the power tower settlement monitoring process based on the key monitoring position; and monitoring and collecting information of the power tower according to the information monitoring point and the adjusted microwave sensing device to obtain a power tower monitoring information database.

[0015] The present application selects the key monitoring position of the power tower in combination with the actual environment, can ensure that the monitoring point covers the key parts of the power tower and the areas prone to problems, can more accurately capture the slight changes of the power tower, and can timely discover potential safety hazards, thereby providing data support for subsequent analysis and decision-making.

[0016] Optionally, the extracting the baseband signal set of the electric tower monitoring point from the electric tower monitoring information library comprises: obtaining channel information, signal amplitude, phase information and frequency data of a single information monitoring point based on the electric tower monitoring information library; analyzing the baseband signal of the single information monitoring point according to the channel information, the signal amplitude, the phase information and the frequency data; and performing integrated analysis and information construction on the baseband signal of the single information monitoring point to obtain the baseband signal set of the electric tower monitoring point.

[0017] The application can comprehensively understand the characteristics of the signal of the monitoring point by obtaining the channel information, signal amplitude, phase information and frequency data of a single information monitoring point from the electric tower monitoring information library, and can accurately grasp the running state of the electric tower at the monitoring point by performing omnidirectional analysis on the signal of the electric tower monitoring point.

[0018] Optionally, the obtaining the distance-angle dimension parameter information of the electric tower monitoring point based on the baseband signal set comprises: performing 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 according to the angle dimension transform information; and obtaining the distance-angle dimension parameter information of the electric tower monitoring point according to 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 can be fused with other types of monitoring data to provide more comprehensive information for the comprehensive monitoring and evaluation of the electric tower and provide information basis for the evaluation of the electric tower structure.

[0020] Optionally, the analyzing the total displacement prediction result of the electric tower according to the distance-angle dimension parameter information and the baseband signal set comprises: establishing a phase analysis formula of the monitoring point in a fixed period based on the distance-angle dimension parameter information; analyzing the phase analysis result of different information monitoring points in a fixed frequency sweeping period through the phase analysis formula of the monitoring point in the fixed period; constructing a monitoring point displacement prediction function by combining the information monitoring points in the electric tower settlement monitoring process and the phase analysis result; obtaining the displacement analysis result of different information monitoring points through the monitoring point displacement prediction function and the baseband signal set; analyzing the displacement of the electric tower by integrating the displacement analysis result of different information monitoring points, and obtaining the total displacement prediction result of the electric tower.

[0021] The application establishes the phase analysis formula of the monitoring point in the fixed period, and analyzes the phase of different information monitoring points in the fixed frequency sweeping period by using the analysis formula, so that the phase information processing of the monitoring point can be completed in a short time, which is beneficial to realizing the real-time monitoring and accurate prediction of the displacement of the electric tower.

[0022] Optionally, the construction settlement monitoring and early warning mechanism is combined with the settlement monitoring and early warning mechanism, the total displacement prediction result and the tower monitoring information base to perform comparative analysis on the tower settlement, so as to realize real-time monitoring and intelligent early warning of the tower settlement, including: setting a settlement benchmark threshold and a grading evaluation mechanism in the settlement monitoring and early warning mechanism; based on the settlement benchmark threshold and the grading evaluation mechanism, performing dynamic comparative analysis on the displacement analysis result of the different information monitoring points and the total displacement prediction result, to obtain a tower settlement analysis result; combining the safety early warning device in the settlement monitoring and early warning mechanism, the tower settlement analysis result and the tower monitoring information base, publishing safety early warning information of the tower settlement; and realizing real-time monitoring and intelligent early warning of the tower settlement according to the safety early warning information.

[0023] Based on the settlement benchmark threshold and the grading evaluation mechanism, the displacement analysis result of the different information monitoring points and the total displacement prediction result are dynamically compared and analyzed, the settlement condition of the tower can be more comprehensively understood, the misjudgment caused by abnormal data of individual monitoring points or prediction error is reduced, and the accuracy of the tower settlement analysis result is improved.

[0024] In order to efficiently execute the microwave perception-based tower settlement monitoring and early warning method provided by the present application, the present application further provides a microwave perception-based tower settlement monitoring and early warning system, which comprises an input device, a processor, an output device and a memory, wherein the input device, the processor, the output device and the memory are connected to each other, the memory is used to store a computer program, the computer program comprises program instructions, the processor is configured to call the program instructions, and the microwave perception-based tower settlement monitoring and early warning method according to the first aspect of the present application is collectively executed. The microwave perception-based tower settlement monitoring and early warning system provided by the present application has compact structure, strong applicability and greatly improved operation efficiency. BRIEF DESCRIPTION OF DRAWINGS

[0025] Figure 1 The flowchart of the microwave perception-based tower settlement monitoring and early warning method of the present application; Figure 2 The structure diagram of the microwave perception-based tower settlement monitoring and early warning system of the present application. DETAILED DESCRIPTION

[0026] The specific embodiments of the present application will be described in detail below, and it should be noted that the embodiments described herein are only used for illustration and do not limit the present application. In the following description, a large number of specific details are set forth in order to provide a thorough understanding of the present application. However, it is obvious to those skilled in the art that the present application does not necessarily have to be implemented with these specific details. In other examples, in order to avoid obscuring the present application, well-known circuits, software or methods are not specifically described.

[0027] Throughout this specification, reference to“one embodiment”,“an embodiment”,“one example” or“an example” means that a particular feature, structure, or characteristic described in connection with the embodiment or example is included in at least one embodiment of the application. The appearances of the phrases“in one embodiment”,“in an embodiment”,“one example” or“an example” in various places in the specification are not necessarily all referring to the same embodiment or example. Furthermore, the particular features, structures, or characteristics can be combined in any suitable

[0028] See Figure 1 To effectively monitor the micro-motion changes of the electric tower and obtain relevant data, the application constructs a specific algorithm to analyze the change situation and settlement condition of the electric tower, compares and analyzes the settlement risk of the electric tower, and identifies early warning. The application provides an electric tower settlement monitoring and early warning method based on microwave perception. The method comprises the following steps: S1, analyze the operation mismatch condition of the microwave perception device, adjust the microwave perception device according to the operation mismatch condition, and obtain the adjusted microwave perception device. The specific setting steps and implementation contents are as follows: To improve the measurement accuracy of the microwave perception device, the measurement error of the device needs to be analyzed, and the microwave perception device is adjusted according to the error condition and mismatch condition to obtain a microwave perception device with better performance.

[0029] The microwave perception device in the embodiment mainly comprises a signal source (signal generator), a transmission line, and a load (such as a power meter, a spectrum analyzer, etc.), and several key parts. In an ideal operating environment, the impedance values of the signal source, the transmission line, and the load are all set to , and the three together form an impedance matching module to ensure efficient and stable transmission and processing of microwave signals.

[0030] However, in real application scenarios, the actual effective values of the impedances of the above components are not fixed and will fluctuate and change to some extent. The instability of the impedances will cause the microwave perception device to be mismatched during operation, eventually causing data measurement errors, and thus affecting the accuracy of the electric tower monitoring information. Next, different mismatch conditions will be analyzed and corresponding adjustment measures will be taken.

[0031] During the operation of the microwave perception device, the mismatch between the load impedance and the transmission line impedance will cause signal reflection, which will affect the measurement accuracy and performance of the device. To accurately analyze the operation mismatch condition of the microwave perception device, the following steps can be taken for detailed analysis: I. Analyzing the operation mismatch of microwave sensing equipment.

[0032] The first step is to analyze the incident power and reflected power of the signal according to the configuration information of the microwave sensing equipment.

[0033] Since the microwave sensing equipment is mainly composed of a signal source (signal generator), a transmission line, and a load (power meter, spectrum analyzer, etc.), during signal transmission, the signal source sends an incident voltage along the transmission line to the load. When transmitted to the load, if the load impedance does not match the characteristic impedance of the transmission line, part of the voltage will be reflected back, forming a reflected voltage and returning to the signal source. If the signal source is in an ideal matching state, the reflected voltage will be completely absorbed and will not be reflected again.

[0034] The incident power travelling to the load satisfies the following calculation formula:

[0035] wherein, P represents the incident power, V represents the incident voltage, Z0 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 inversely proportional to the characteristic impedance of the transmission line , and the incident power reflects the power transmitted by the signal source to the load.

[0036] The calculation formula of the power reflected by the load is as follows:

[0037] wherein, P represents the reflected power, V represents the reflected voltage, Z0 represents the characteristic impedance of the transmission line, Γ represents the reflection coefficient. The reflected power is the power carried by the reflected signal due to the mismatch of the load impedance.

[0038] The above reflection coefficient satisfies the following condition , which reflects the matching degree of the load impedance and the transmission line impedance, and its value range is . When , it means that the load and the transmission line are completely matched, and there is no reflected power at this time ; when , it means that the load and the transmission line are completely mismatched, and the reflected power reaches the maximum value .

[0039] The second step is to obtain the actual load power of the microwave sensing device based on the incident power and reflected power.

[0040] Actual power obtained on the load The difference between the incident power and the reflected power is:

[0041] Will Substituting into the above formula, we get:

[0042] And because Furthermore, we can obtain:

[0043] in, This indicates the actual power received by the load.

[0044] 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.

[0045] The third step is to construct a formula for calculating mismatch loss based on the actual power of the load.

[0046] 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:

[0047] in, Indicates mismatch loss. This indicates the actual power received by the load. This indicates the incident power.

[0048] Bundle Substituting, we get:

[0049] in, Indicates mismatch loss. This represents the reflection coefficient.

[0050] 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.

[0051] Further, there is measurement error in actual measurement process, assuming that the measured reflection coefficient is , the actual reflection coefficient is , the measurement error coefficient is introduced , and satisfies:

[0052] wherein, represents the measured value of the reflection coefficient, represents the measurement error coefficient, represents the actual value of the reflection coefficient, and the value range of the above is between , and the specific value can be adjusted and determined according to the accuracy of the actual measurement equipment.

[0053] Based on this, the mismatch loss calculation formula is optimized to obtain the optimized mismatch loss and satisfies the following relationship:

[0054] Substituting into the above formula can obtain:

[0055] wherein, represents the optimized mismatch loss, represents the measurement error coefficient, represents the measured value of the reflection coefficient, represents the actual value of the reflection coefficient.

[0056] The measurement error coefficient is mainly used to correct the measured reflection coefficient, so as to improve the accuracy of the mismatch loss calculation result. At the same time, the measurement error coefficient is introduced, so that the calculation of the mismatch loss is closer to the actual situation, and the influence of the measurement error on the analysis result is reduced.

[0057] The fourth step obtains the mismatch loss result of the microwave perception device through the mismatch loss calculation formula.

[0058] Substituting the actual measured reflection coefficient or the actual reflection coefficient determined according to the actual situation and the measurement error coefficient into the optimized mismatch loss calculation formula , wherein the mismatch loss result of the microwave perception device can be obtained by calculation.

[0059] The fifth step analyzes the load impedance mismatch condition of the microwave perception device based on the mismatch loss result.

[0060] In an optional embodiment, if the mismatch loss is small , indicating that the load impedance is well matched with the transmission line impedance, the reflection coefficient is close to 0, the load can effectively absorb the incident power, the operation state of the equipment is relatively ideal, and the influence of measurement error on the result is small.

[0061] If the mismatch loss is moderate , it indicates that there is a certain mismatch between the load impedance and the transmission line impedance, and the reflection coefficient fluctuates within a certain range. At this time, the microwave perception equipment can work normally, but it will have a certain impact on the measurement accuracy. Therefore, the change of the load impedance needs to be focused on, and appropriate adjustment needs to be made if necessary.

[0062] If the mismatch loss is large , it means that the load impedance is seriously mismatched with the transmission line impedance, and the reflection coefficient is close to . Most of the incident power is reflected back, and the actual power obtained by the load is very small. In this case, the measurement accuracy of the microwave perception equipment will be greatly affected, and the connection of the load and the transmission line needs to be checked immediately and appropriate measures need to be taken to adjust.

[0063] Through the above five steps, the running mismatch condition of the microwave perception equipment can be comprehensively and accurately understood, providing reference basis and adjustment direction for the optimization adjustment and performance improvement of the equipment.

[0064] II. Analysis of the running mismatch condition of the microwave perception equipment.

[0065] In the running process of the microwave perception equipment, the mismatch between the signal source and the load impedance will cause signal reflection, which will affect the performance and measurement accuracy of the equipment. The following steps are taken for research.

[0066] The first step is to standardize the definition of the signal source and load parameters of the microwave perception equipment and obtain the parameter definition information.

[0067] In order to comprehensively and accurately analyze the two-end mismatch scenario of the signal source and the load, and quantify the influence of phase uncertainty on power transmission, the related parameters of the microwave perception equipment are standardized in this embodiment.

[0068] The signal source reflection coefficient is defined as , where represents the signal source reflection coefficient, represents the actual output impedance of the signal source, represents the characteristic impedance of the transmission line. This coefficient reflects the matching degree of the signal source output impedance and the transmission line characteristic impedance, and its value range is between , when , it means that the signal source output impedance is completely matched with the transmission line characteristic impedance; when , it means complete mismatch.

[0069] The load reflection coefficient is defined as wherein, represents the load reflection coefficient, is the load actual impedance, represents the characteristic impedance of the transmission line, which reflects the matching condition of the load impedance and the characteristic impedance of the transmission line, and the value range is also between and represents that the load and the transmission line are completely matched, represents complete mismatch.

[0070] The double-end coupling reflection coefficient is defined as wherein represents the double-end coupling reflection coefficient, which represents the strength of the round-trip reflection of the signal between the source and the load, and the coefficient comprehensively reflects the reflection characteristics of the signal source and the load and the coupling degree between them.

[0071] The phase shift factor can be measured by a vector network analyzer . The phase shift factor is related to the phase angle of the signal source and the load reflection coefficient, and the maximum / minimum power transmission boundary can be calculated by measurement, so as to more comprehensively understand the phase change of the signal in the transmission process.

[0072] The second step is to establish a power transmission equation according to the microwave signal reflection of the microwave perception device.

[0073] When the signal source and the load impedance are both unmatched, the signal reflected by the load returns to the signal source and is not absorbed, but is reflected back to the load again. The relevant reflected signals may be superimposed or cancelled at the load, depending on the signal phase. In the case of slight mismatch between the signal source and the load impedance, the amplitude of each additional reflection is much smaller than the first round-trip reflection between the load and the signal source, so this embodiment only considers the first round-trip reflection.

[0074] The signal source voltage of the incident wave is leaves the signal source and propagates to the load, generating an incident voltage at the load end. After being reflected back to the signal source, it is reflected to the load again to form a second incident wave. At this time, there are two waves incident on the load, and the following relationship exists:

[0075] Therefore, we have

[0076] wherein, the uncertainty of the sign of the reflection term indicates the uncertainty of the superposition or cancellation of the reflected wave.

[0077] The above Taking square and combining the mismatch loss at the signal source and load, the power transmission equation can be obtained and satisfies the following relationship:

[0078] The numerator of the power transmission equation embodies the influence of the mismatch loss, indicating that a given reflection coefficient will result in the loss of the corresponding power of the load; the denominator represents the uncertainty of the mismatch, and the power transmission has uncertainty due to the positive or negative sign in the denominator, and the actual power transmission may be between the two extreme cases. From the measurement point of view, the maximum and minimum power transmission can be obtained, and the maximum and minimum errors that may be caused by the impedance matching problem can be determined.

[0079] The logarithmic form analysis of the power transmission equation is convenient for subsequent separate consideration of each error term, and further

[0080] According to the multiplication law of logarithm , the expansion of can be obtained ; At the same time, according to the power law of logarithm , the expansion of is ; Substituting the above expansion results into , we can get ;

[0081] For the problem of mismatch of signal source and load impedance, the impedance of signal source and load needs to be adjusted at the same time. For the signal source, the output impedance can be changed by adjusting its internal circuit parameters; for the load, impedance matching network can also be used for impedance transformation. In addition, impedance matching devices such as directional coupler, power divider, etc. can be used to improve the impedance matching between the signal source and the load. In actual measurement, in addition to considering the problem of impedance mismatch, it is also necessary to pay attention to keeping the joint clean and ensuring good contact to avoid introducing measurement errors due to joint problems.

[0082] The third step is to optimize the power transmission equation based on the parameter definition information to obtain a more accurate and comprehensive power transmission analysis expression.

[0083] Substituting the parameter definition into the power transmission equation, the optimized power transmission analysis expression can be obtained:

[0084] Among them, the numerator can quantify the double-end independent mismatch loss, and the denominator can represent the phase-dependent uncertainty gain. ​

[0085] due to phase shift factor and double-ended coupling reflection coefficient satisfy the following relationship;

[0086] where and represent the phase angles of the signal source and load reflection coefficients, respectively.

[0087] Substituting them into the power transmission equation, we get the further optimized power transmission equation:

[0088] The logarithmic form of the optimized power transmission equation is extended:

[0089] By itemized quantization, the contributions of signal source mismatch, load mismatch, and phase coupling to the total error can be evaluated independently, which facilitates more accurate positioning of the problems of microwave sensing devices.

[0090] The fourth step analyzes the mismatch between the signal source and load impedance through the power transmission analysis expression and parameter definition information.

[0091] According to the power transmission ratio analysis: the power transmission ratio is obtained by measurement or calculation, and compared with the ideal power transmission ratio (i.e., the power transmission ratio when the signal source and load are perfectly matched, which is ). If is significantly less than 1, it indicates that there is an impedance mismatch problem.

[0092] Combined with the reflection coefficient analysis: according to the values of the signal source reflection coefficient and the load reflection coefficient , the matching degree of the signal source and load is judged. If or is close to , it indicates that the corresponding signal source or load is severely mismatched with the transmission line; if it is close to 0, it indicates good matching.

[0093] Consider the phase factor analysis: observe the influence of the phase shift factor on power transmission. Different values will cause the power transmission ratio to change between the maximum and minimum values. By analyzing this change rule, the specific influence of phase uncertainty on power transmission can be understood.

[0094] 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.

[0095] Finally, the microwave sensing device was adjusted based on the above-mentioned operational mismatch, and the adjusted microwave sensing device was obtained.

[0096] 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.

[0097] 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.

[0098] 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:

[0099] 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.

[0100] 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 When the load impedance is adjustable, such as a variable resistor, a variable capacitor, etc., the impedance value can be adjusted to be close to the characteristic impedance of the transmission line by adjusting the load parameters. It can be negative. With the same impedance ratio term, it can be ensured that the network resonates at the target frequency to achieve impedance transformation.

[0101] If the load is adjustable, such as a variable resistor, a variable capacitor, etc., the impedance value can be adjusted to be close to the characteristic impedance of the transmission line by adjusting the load parameters. For a variable resistor, the resistance value can be changed by rotating the resistance adjustment knob; for a variable capacitor, the capacitance value can be adjusted by changing the distance or area of the capacitor plates.

[0102] Insert an impedance matching device, such as a directional coupler, a power divider, etc., between the signal source and the load. The directional coupler can couple a portion of the signal power to the load while achieving impedance matching between the signal source and the load, and the power divider can evenly distribute the input signal power to multiple output ports, with each output port impedance matching the transmission line impedance.

[0103] The second step is to adjust the circuit parameters, impedance network and phase offset of the microwave sensing device according to the mismatch between the signal source and the load impedance, and obtain an impedance network and a compensated offset factor that is close to the characteristic impedance of the transmission line.

[0104] Internal circuit parameter adjustment: for the signal source part of the microwave sensing module, determine the key parameters that affect the output impedance, such as the bias current of the transistor, the resistance and capacitance 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 .

[0105] Load impedance adjustment and impedance matching network design: according to the actual impedance of the microwave sensing module load and the characteristic impedance of the transmission line, design the corresponding impedance matching network, the impedance network can have single or multi-section matching network, in actual application can choose the appropriate type according to the load characteristics and working frequency, for the frequency is lower, the bandwidth requirement is not high, can use single section quarter wavelength transmission line matching; for the frequency is higher, the bandwidth requirement is wider, can use multi-section matching network.

[0106] Phase offset factor measurement and compensation: in the embodiment, the microwave sensing module is measured using a vector network analyzer, and the phase angles of the signal source and load reflection coefficients and are accurately obtained, and the phase offset factor is calculated.

[0107] Designing a phase compensation circuit: according to the phase offset factor, a phase compensation circuit is designed, which can be realized by using phase shifters, delay lines and other elements. For example, a variable phase shifter can be used to change the phase shift by adjusting its control voltage, thereby compensating for the phase offset and maintaining a stable phase relationship of the signal during transmission.

[0108] The third step is to adjust the microwave sensing device based on the load impedance, characteristic impedance, adaptive impedance network and compensated offset factor, and finally obtain the adjusted microwave sensing device.

[0109] The technologies and elements involved in the above adjustment strategy, such as impedance matching network, variable load element and impedance matcher, are mature and reliable in the microwave field. Whether it is through adjusting internal circuit parameters, using impedance transformation network, or using impedance matcher, there is theoretical basis and practical experience for reference, providing technical support for microwave sensing device adjustment.

[0110] The measurement and compensation technology of phase offset factor is widely used in modern microwave measurement and communication systems. The phase information can be accurately measured by vector network analyzer and other measuring instruments, and various phase control elements such as phase shifters and delay lines also have high performance and reliability. By reasonably designing and integrating the phase compensation circuit, the influence of phase uncertainty on power transmission can be effectively controlled. At the same time, the cost of the above impedance matching network and variable load element is relatively low, and it can be customized and selected according to actual needs.

[0111] In summary, based on the adjustment of microwave sensing device under the condition of mismatch between signal source and load impedance, the use performance of microwave sensing device can be effectively improved, the power transmission efficiency can be improved, and the information measurement error can be reduced, providing more reliable technical support for the application of microwave sensing device.

[0112] S2, deploy the above adjusted microwave sensing device, and monitor and collect information of the tower through the adjusted microwave sensing device to obtain a tower monitoring information database, the specific steps and implementation contents are as follows: The first step is to deploy the adjusted microwave sensing device based on the actual environmental conditions.

[0113] Investigate the actual situation of the environment where the tower is located, investigate 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; analyze possible interference sources in the surrounding area, such as high-voltage lines, large metal facilities, radio transmission towers, etc.

[0114] Before the device is deployed, the adjusted microwave sensing device needs to be debugged, including signal transmission power calibration, receiving sensitivity test, antenna directionality adjustment, etc., to ensure that the microwave sensing device can work normally under various environmental conditions.

[0115] Next, according to the characteristics of the tower base environment, the optimal installation position of the microwave sensing device is determined. The position can be selected around the tower base, which is relatively open, unobstructed and has less interference, to ensure that the microwave signal emitted by the device can effectively cover the tower base area and accurately receive the reflected signal. During installation, follow the device installation instructions to ensure that the device is installed firmly and horizontally, avoiding inaccurate monitoring data due to unstable device installation. At the same time, the influence of the terrain on the microwave signal propagation should be considered, and the height and angle of the device should be adjusted reasonably to reduce signal obstruction and reflection interference.

[0116] After the device is installed, a function verification test is performed. By emitting a specific test signal, it is checked whether the device can normally emit and receive microwave signals, and whether the phase, frequency and other parameter changes of the reflected signal meet the expected values. Problems found during verification are adjusted and repaired in a timely manner to further ensure that the device performance is in the best state.

[0117] The second step is to select the key monitoring position of the tower based on the actual environmental conditions.

[0118] The overall structure of the tower is analyzed, including but not limited to the type of tower (angle steel tower, steel pipe tower), height, tower section, cross arm structure, etc. The stress characteristics and deformation law of different components of the tower under load, wind action and geological changes are understood, and the key positions in the tower structure that are prone to settlement, deformation and other problems are determined.

[0119] Referring to historical geological disaster data, tower operation and maintenance records, etc. in the area where the tower is located, the position and cause of previous tower settlement, inclination and other accidents are further analyzed, combined with the actual operation status and environmental conditions of the current tower, to predict high-risk areas that may have problems, and the relevant areas are considered as the focus of key monitoring positions.

[0120] The key monitoring position of the tower is determined based on the actual situation and the overall structure of the tower. In this embodiment, the above-mentioned positions include the tower foundation, the connection between the tower body and the foundation, the key nodes of the tower body (the connection between the cross arm and the tower body, the tower body slope position, etc.), to ensure effective monitoring of the overall structure of the tower.

[0121] The third step is to set the information monitoring point in the tower settlement monitoring process based on the key monitoring position.

[0122] According to the key monitoring position, the information monitoring point layout planning is made. Considering the geometric shape of the electric tower, the structural symmetry and the monitoring accuracy requirements and other factors, the number and distribution density of the monitoring points are reasonably determined. In the key area of the key monitoring position, the number of monitoring points is appropriately increased to improve the accuracy and reliability of the monitoring data. In an optional embodiment, a plurality of monitoring points are uniformly arranged at a certain interval around the electric tower to comprehensively monitor the settlement of the electric tower.

[0123] At the same time, an obvious identification is set for each information monitoring point to facilitate subsequent monitoring and maintenance work. In the embodiment, the identification contains the monitoring point number, position information and the like, and is made of a material with good durability to ensure that the identification is clear and visible in the long-term monitoring process. At the same time, a detailed monitoring point file is established to record the geographic position, coordinate information, surrounding environment and the like of each monitoring point to provide basic data for subsequent data analysis and processing.

[0124] The information monitoring point is associated with the deployed microwave sensing device. The corresponding microwave sensing device number and monitoring parameter setting of each monitoring point are determined to ensure that the device can accurately collect the relevant information of the monitoring point. In the electric tower settlement monitoring and early warning system, a corresponding relationship database of the monitoring point and the device is established to facilitate data query and management.

[0125] In the fourth step, the electric tower is monitored and information is collected according to the information monitoring point and the adjusted microwave sensing device to obtain an electric tower monitoring information library.

[0126] According to the operation characteristics and monitoring requirements of the electric tower, an information monitoring scheme is made. In this embodiment, the monitoring frequency, monitoring time period and the like are determined, wherein for the electric tower in a complex geological condition area, the monitoring frequency can be appropriately increased, and the monitoring is performed multiple times a day; for the electric tower with stable operation and good geological condition, the monitoring frequency can be appropriately reduced, and the monitoring is performed 3-4 times a week. At the same time, the collection mode and transmission mode of the monitoring data are determined to ensure that the data can be timely and accurately transmitted to the data processing center.

[0127] According to the information monitoring scheme, the adjusted microwave sensing device is started to monitor the electric tower in real time. The device continuously emits microwave signals and receives reflected signals, analyzes and processes the phase, frequency and the like of the reflected signals through the built-in data processing module, and extracts information related to the settlement and micro-motion of the electric tower. The collected monitoring data is transmitted to the data processing center in real time to ensure the timeliness and integrity of the data. In the data transmission process, encryption technology is used to ensure the security of the data to prevent data leakage and tampering.

[0128] The data processing center in the electric tower settlement monitoring and early warning system receives the monitoring data and performs preprocessing work thereon, including but not limited to data cleaning, denoising, normalization and the like, so as to improve the quality of the monitoring data.

[0129] The monitoring data after processing and analysis is stored in the electric tower monitoring information library according to certain format and specification. The information library should have perfect data structure, and can conveniently store, query and manage various types of monitoring data, mainly including monitoring time, monitoring point position, monitoring parameter value, data analysis result and the like. At the same time, the information library is equipped with corresponding data retrieval and statistical analysis functions, so as to facilitate users to quickly obtain the required monitoring information, and provide decision support for the operation, maintenance and management of the electric tower.

[0130] Through the above implementation steps, the effective deployment and application of the adjusted microwave sensing device in the electric tower monitoring can be ensured, and a comprehensive and accurate electric tower monitoring information library is constructed, which provides data basis and information reference for the electric tower settlement monitoring and safety early warning.

[0131] S3, extracting a baseband signal set of the electric tower monitoring point from the above electric tower monitoring information library, obtaining distance-angle dimension parameter information of the electric tower monitoring point based on the baseband signal set, and analyzing total displacement prediction results of the electric tower according to the distance-angle dimension parameter information and the baseband signal set, the specific implementation contents are as follows: First, extract the baseband signal set of the electric tower monitoring point from the above electric tower monitoring information library.

[0132] The first step is to obtain the channel information, signal amplitude, phase information and frequency data of a single information monitoring point based on the electric tower monitoring information library.

[0133] Based on the implementation content, a total of target monitoring points are set in the electric tower settlement monitoring process, and the above key nodes cover the electric tower foundation, the connection part between the tower body and the foundation, the key nodes of the tower body and the like, so as to ensure effective monitoring of the overall structural safety of the electric tower.

[0134] At the same time, each target monitoring point is configured with information transmission channels, and the selection of the information transmission channels should consider factors such as transmission stability and anti-interference ability, so as to ensure that the monitoring data can be accurately and timely transmitted.

[0135] According to the electric tower monitoring information library, the sweep center frequency is set to , and the wavelength parameter can be calculated by using the formula , wherein represents the speed of light . The wavelength parameter plays an important role in subsequent phase analysis and displacement calculation, so the sweep center frequency The measurement accuracy of the system.

[0136] To eliminate system drift, a reference phase is introduced , and defined , wherein represents the reference channel phase, and the phase reference calibration can effectively eliminate the phase error caused by system clock drift, temperature change and other factors, and improve the accuracy of monitoring data.

[0137] and determine the baseband signal amplitude , beat frequency , modulation phase related to vibration displacement and additive Gaussian white noise term corresponding to different information monitoring points of the information transmission channel, which will be used in the subsequent baseband signal analysis and modeling process.

[0138] The phase difference method is used to calculate the phase change of the reflected signal, and by comparing the phase difference of the reflected signal at different times, part of the system error can be effectively eliminated, and the accuracy of the phase measurement can be improved.

[0139] The frequency offset is determined by spectrum analysis, which can convert the signal from time domain to frequency domain, and accurately obtain the frequency offset by analyzing the peak position and frequency distribution in the spectrum.

[0140] The second step is to analyze the baseband signal of a single information monitoring point according to the channel information, signal amplitude, phase information and frequency data.

[0141] Based on the target data set and the microwave vibration measurement method, the vibration of the target is inverted by using the interference phase modulation information, and the displacement change of the adjacent time monitoring point in the radar line-of-sight direction satisfies the following relationship:

[0142] , wherein represents the displacement change of the target in the radar line-of-sight direction at adjacent time, represents the wavelength corresponding to the sweep center frequency, represents the circumference, represents the interference phase change at adjacent time, represents the time variable.

[0143] However, the above formula only has one-dimensional distance resolution capability, when different target monitoring points are in similar or same distance units, two components with similar beat frequency are easily coupled or even aliasing, which leads to difficulty in accurately distinguishing different monitoring points, serious coupling interference between target components, and significant increase in measurement error, even serious distortion of displacement measurement waveform.

[0144] To solve the above problems, the embodiment adopts a distance and angle joint mode to realize effective identification, positioning and information extraction of the tower displacement, considers the distance and angle information of different information monitoring points, can effectively enhance the resolution capability of the information monitoring point, suppress the coupling interference, and improve the accuracy and reliability of the monitoring data and analysis results.

[0145] Based on the target data set of the microwave perception module, the single monitoring point in the frequency sweeping period is The baseband signal analysis model of the information transmission channel is based on the analysis of the baseband signal of a single information monitoring point, and satisfies the following relationship:

[0146] Among them, represents the baseband signal output by different information transmission channels for a single target monitoring point, represents the information transmission channel number, represents the number of information transmission channels in the tower monitoring process, represents the baseband signal amplitude generated by the information transmission channel, represents the imaginary unit, represents the circular constant, represents the beat frequency generated by the information transmission channel, represents the modulation phase related to the vibration displacement of the information transmission channel, represents the additive white Gaussian noise term.

[0147] The third step is to integrate and analyze the baseband signal of a single information monitoring point and construct information to obtain the baseband signal set of the tower monitoring point.

[0148] Combining the baseband signals of all information monitoring points can construct the baseband signal set of the target monitoring point in the tower settlement monitoring process, which is represented in matrix form in the embodiment:

[0149] Among them, represents the global baseband signal matrix, represents the discrete time sequence of the baseband signal of different information transmission channels. The matrix structure is clear, each row corresponds to a channel, each column corresponds to a monitoring point, and the element is a discrete sampling signal, which is convenient for subsequent monitoring data processing and extraction analysis.

[0150] 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.

[0151] 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.

[0152] 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.

[0153] The baseband signal matrix is ​​known to satisfy the following relationship:

[0154] 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.

[0155] 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.

[0156] 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.

[0157] Through the above two-dimensional FFT processing, the joint dimension analysis of distance-angle can be performed. Based on the signal model analysis, it can be known that the electric tower vibration displacement can be tracked and acquired based on the joint dimension non-linear demodulation and interference phase. In the joint dimension analysis process, the signal phases at different distances and angles contain the information of the electric tower vibration displacement, and by performing the non-linear demodulation processing on the above phases, the vibration displacement of the electric tower at different positions can be extracted.

[0158] The second step is to obtain the distance dimension phase rotation factor based on the distance dimension transformation information.

[0159] The distance dimension phase rotation factor is mainly used for describing the rotation characteristics of the signal phase in the distance dimension, and reflects the phase change of the signal at different distances. By introducing the distance dimension phase rotation factor, the signal in the distance dimension can be phase corrected and adjusted, so as to more accurately analyze the distance related parameter information.

[0160] The distance dimension phase rotation factor is as follows:

[0161] Wherein, represents an imaginary unit, represents a frequency index, represents a distance dimension FFT resolution, represents the number of points of the distance dimension FFT, represents a distance dimension correction coefficient. In the calculation process, the accuracy of each parameter needs to be ensured to ensure the effectiveness of the phase rotation factor.

[0162] The third step is to obtain the angle dimension phase rotation factor according to the angle dimension transformation information.

[0163] The angle dimension phase rotation factor can describe the rotation characteristics of the signal phase in the angle dimension, and reflects the phase change of the signal at different angles. By introducing the angle dimension phase rotation factor, the signal in the angle dimension can be phase corrected and adjusted, which is helpful for more accurately analyzing the angle related parameter information.

[0164] The above angle dimension phase rotation factor is as follows:

[0165] Wherein, represents an imaginary unit, represents an angle index, represents an angle dimension FFT resolution, represents the number of points of the angle dimension FFT, represents an angle dimension correction coefficient.

[0166] The fourth step is to obtain the distance-angle dimensional parameter information of the electric tower monitoring point according to the distance dimension transformation information, the angle dimension transformation information, the distance dimension phase rotation factor and the angle dimension phase rotation factor.

[0167] The distance dimension transformation information and the angle dimension transformation information provide the frequency distribution characteristics of the signal in the distance and the angle, and the distance dimension phase rotation factor and the angle dimension phase rotation factor are used for correcting and adjusting the signal phase.

[0168] Through the comprehensive processing of the above information, the distance-angle dimensional parameter information of the electric tower monitoring point can be obtained. The above parameter information includes but is not limited to the vibration displacement, the phase change and the frequency offset of the electric tower at different distances and angles.

[0169] Through the above steps, the distance-angle dimensional parameter information of the electric tower monitoring point can be accurately obtained based on the baseband signal set, which provides data support for the effective monitoring of the electric tower settlement and the structural safety evaluation.

[0170] Finally, the total displacement prediction result of the electric tower is analyzed according to the distance-angle dimensional parameter information and the baseband signal set.

[0171] The first step is to establish a phase analysis formula of the monitoring point in a fixed period based on the distance-angle dimensional parameter information.

[0172] The phase of the monitoring point in a fixed period is analyzed, and the phase information of the target in the distance-angle joint domain is extracted. The above information can reflect the vibration displacement of the target, and provides key data for subsequent displacement prediction.

[0173] For different information monitoring points in the electric tower settlement monitoring process, the phase calculation formula in t frequency sweeping periods is as follows:

[0174] Wherein, represents the phase of the i-th information monitoring point in the t-th frequency sweeping period, represents the complex phase operation, represents the number of target monitoring points in the electric tower settlement monitoring process, represents the number of information transmission channels in the electric tower monitoring process, represents the number of target monitoring points, represents the number of information transmission channels, represents the i-th sampling signal of the i-th channel in the t-th frequency sweeping period, ​​​​​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.

[0175] The complex phase operation can be used to demodulate the phase information of the monitoring point in the distance-angle joint domain through two-dimensional FFT. That is, first, a two-dimensional FFT transformation is performed on the baseband signal set to transform the signal from the time-space domain to the frequency-angle domain. Then, the phase information of the corresponding position is extracted from the transformed result. This phase information can reflect the vibration and displacement characteristics of the monitoring point.

[0176] 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.

[0177] 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.

[0178] 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.

[0179] 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.

[0180] Line of sight displacement at different target monitoring points It can be represented as:

[0181] 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.

[0182] wherein the sliding average phase is obtained by averaging the phase values within a certain time window, which 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 the value range is between 0 and 1, which is mainly used to adjust the confidence of the displacement prediction result.

[0183] The fourth step obtains the displacement analysis results of different information monitoring points through the monitoring point displacement prediction function and the baseband signal set.

[0184] The relevant data (phase value, effective wavelength, etc.) in the monitoring point displacement prediction function and the baseband signal set are input into the displacement prediction model; according to the monitoring point displacement prediction function, the line-of-sight direction displacement of each information monitoring point is calculated in turn, and the calculated displacement results are recorded, including but not limited to monitoring point number, displacement value, calculation time, etc. information, so as to facilitate subsequent analysis and query, and the displacement analysis results of different information monitoring points are obtained.

[0185] The fifth step integrates the displacement analysis results of different information monitoring points to analyze the displacement of the electric tower and obtains the total displacement prediction result of the electric tower.

[0186] The displacement analysis results of different information monitoring points are integrated, and the position distribution and importance of each monitoring point are comprehensively considered. In this embodiment, a weighted average method is used to calculate the total displacement of the electric tower, wherein the weighted average method can determine the weight coefficient according to the distance between the monitoring point and the key part of the electric tower, the influence degree of the monitoring point on the safety of the electric tower structure, etc. so that the total displacement prediction result can better reflect the actual displacement of the electric tower.

[0187] Finally, the electric tower feature parameter information, the displacement analysis results of different information monitoring points, and the total displacement prediction result are digitally converted according to the preset coding rule to generate a digital signal that can accurately reflect the micro-motion changes of the electric tower foundation. In this embodiment, the coding 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. Binary coding method can be used, the number of coding bits is determined according to the value range of the feature parameters, and each feature parameter is mapped to a unique binary code group. At the same time, in order 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.

[0188] After converting the feature parameters into digital signals according to the coding rule, the digital signals are stored and managed. Suitable storage media (database, file system) can be selected, and a perfect data storage structure is established to facilitate subsequent query, analysis and application, and to provide strong guarantee for real-time monitoring and safe operation of the electric tower.

[0189] S4, in order to realize the accurate control and timely warning of the settlement of the electric tower, a settlement monitoring and warning mechanism is constructed. The settlement of the electric tower needs to be compared and analyzed in combination with the settlement monitoring and warning mechanism, the total displacement prediction result and the electric tower monitoring information base. The specific implementation steps are as follows: The first step is to set the settlement reference threshold value and the hierarchical evaluation mechanism in the settlement monitoring and warning mechanism.

[0190] In the setting process of the settlement reference threshold value, the design requirements of the electric tower, the geological conditions and the historical monitoring data and other factors need to be considered comprehensively, so as to determine the safety threshold value of the electric tower foundation settlement. The design specification settlement tolerance value of the electric tower (such as referring to GB50010-2010 Concrete Structure Design Specification), the soil compression modulus provided in the geological exploration report and the historical 5-year average settlement rate and other key element information can be referred to. Further, the weighted average method can be used to calculate the initial threshold value, so as to ensure the scientificity and rationality of the threshold value setting.

[0191] The embodiment constructs a multi-level hierarchical evaluation mechanism, which divides the safety threshold value into different levels to correspond to different degrees of settlement risk. The hierarchical evaluation mechanism includes the warning threshold level, the alarm threshold level and the limit threshold level. The relevant contents are as follows: The warning threshold level is set to 50% of the settlement reference threshold value. When the micro-motion change digital signal value exceeds this threshold value, the system automatically sends a yellow warning signal.

[0192] The alarm threshold level is set to 70% of the settlement reference threshold value. If the signal value exceeds this threshold value, the system sends an orange alarm signal.

[0193] The limit threshold level is set to 100% of the settlement reference threshold value. Once the signal value reaches or exceeds this threshold value, the system triggers a red emergency power-off operation.

[0194] At the same time, considering the influence of seasonal geological changes on the settlement reference threshold value, the size of the settlement reference threshold value is automatically optimized based on the newly collected data every quarter by using the LSTM time series model, so that the threshold value can dynamically adapt to the changes of the actual geological conditions.

[0195] In addition, the threshold value needs to be recorded and data managed. The set safety threshold value is accurately stored in the system storage unit for subsequent query and call; in the monitoring process, the digital signal value corresponding to the micro-motion change of the electric tower foundation is recorded in real time, and the time, degree and other key information of each threshold value exceeding are recorded in detail, providing complete data support for subsequent analysis and tracing; a structured database table is established, mainly including the following key fields: monitoring point ID, timestamp, settlement amount, triggered threshold level, processing state and coordinate information.

[0196] The second step is to dynamically compare and analyze the displacement analysis results of different information monitoring points and the total displacement prediction results based on the settlement benchmark threshold and the grading evaluation mechanism to obtain the electric tower settlement analysis results.

[0197] Firstly, the line-of-sight displacement is compared. The line-of-sight displacement of different information monitoring points is compared with the benchmark threshold one by one to find potential safety hazards in the electric tower area corresponding to different information monitoring points in time.

[0198] Then, real-time data analysis is performed. The system data processing unit continuously and real-timely analyzes the digitized micro-motion change data and compares them with the stored safety threshold to real-timely master the actual situation of the electric tower foundation settlement.

[0199] Meanwhile, multi-dimensional comparison and analysis are performed. Spatial dimension analysis: the settlement differences of different monitoring points of the same electric tower are compared to accurately identify the non-uniform settlement risk by analyzing the inconsistency of the settlement amounts of the monitoring points, thereby providing a basis for subsequent maintenance and processing. Time dimension analysis: the change trend of the settlement rate is analyzed to predict the settlement amount and change of the electric tower area in the next 48-72 hours by using data analysis methods, which is beneficial to making preparations in advance. Environmental dimension analysis: the environmental data such as temperature, humidity, and rainfall of the area where the electric tower is located are combined to comprehensively analyze the electric tower settlement monitoring results, eliminate the interference of environmental factors on the settlement, and ensure the accuracy of the electric tower settlement prediction results.

[0200] The third step is to release the safety warning information of the electric tower settlement by combining the safety warning device in the settlement monitoring and warning mechanism, the electric tower settlement analysis results, and the electric tower monitoring information library.

[0201] The information fed back by the safety warning device in the settlement monitoring and warning mechanism, the electric tower settlement analysis results, and the related data in the electric tower monitoring information library are comprehensively integrated to further ensure the integrity and accuracy of the information.

[0202] According to the integrated information, the system platform timely and accurately releases the safety warning information of the electric tower settlement according to the established grading evaluation mechanism. In the embodiment, the warning information includes but is not limited to the electric tower location, the settlement situation, the trigger threshold level, and the corresponding processing suggestions and other key contents, so that relevant personnel can quickly understand the situation and take effective measures.

[0203] The fourth step is to realize the real-time monitoring and intelligent warning of the electric tower settlement according to the safety warning information.

[0204] The monitoring equipment and technical means are used to continuously monitor the settlement of the electric tower in real time, so as to ensure that any change information and data about the settlement of the electric tower can be captured in time. Based on the real-time monitoring data and the preset grading evaluation mechanism, the system automatically performs intelligent analysis and judgment. Once it is found that the settlement reaches or exceeds the corresponding threshold, the corresponding early warning signal is triggered, and the early warning information is pushed to the relevant personnel in time, so that the intelligent early warning function of the electric tower settlement is realized. At the same time, the system should have the function of automatically recording and storing the early warning information, so as to facilitate subsequent query and statistical analysis.

[0205] Through the above implementation steps, a perfect, scientific and feasible electric tower settlement monitoring and early warning mechanism can be constructed, real-time monitoring and intelligent early warning of the electric tower settlement are realized, and the safe work and stable operation of the electric tower are effectively ensured.

[0206] Please refer to Figure 2 In an optional embodiment, in order to efficiently execute the microwave perception-based electric tower settlement monitoring and early warning method provided by the present application, the present application further provides a microwave perception-based electric tower settlement monitoring and early warning system. The system includes a processor, an input device, an output device and a memory, which are connected to each other. The memory is used to store a computer program, the computer program includes program instructions, and the processor is configured to call the program instructions to execute the specific steps of the microwave perception-based electric tower settlement monitoring and early warning method and related embodiments provided by the present application. The microwave perception-based electric tower settlement monitoring and early warning system of the present application has a complete structure and is objective and stable.

[0207] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement to part or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application, and they should be covered in the scope of the claims and the specification of the present application.

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. The settlement situation of power towers 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.

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 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.

8. The method for monitoring and early warning of power tower settlement based on microwave sensing according to claim 7, 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.

9. 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 stores a computer program, which includes program instructions. The processor is configured to invoke the program instructions to execute the microwave sensing-based power tower settlement monitoring and early warning method as described in any one of claims 1-8.

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