Power pole inclination detection method and system

Abstract

The invention relates to the technical field of power pole detection, in particular to a power pole inclination detection method and system. The method comprises the following steps: acquiring lifting point inclination parameters acquired by each lifting point inclination sensor mounted on a power pole and each marker post inclination angle measured by an inclination sensor mounted on a marker post between two adjacent lifting points; determining each differential motion inclination parameter based on each lifting point inclination parameter; determining each spatial attitude parameter based on the inclination angle of each marker post; comparing each differential inclination parameter and each space attitude parameter with a corresponding preset early warning threshold value and a corresponding preset alarm threshold value respectively to obtain a comparison result of each differential inclination and a comparison result of each space attitude; and performing detection processing on the comparison result of each differential motion inclination and the comparison result of each space attitude to obtain an electric pole inclination detection result. The objective of the invention is to solve the problem that the inclination of the power pole cannot be accurately detected in the prior art.

Description

Technical Field

[0001] This invention relates to the field of power pole inspection technology, and specifically to a method and system for detecting the tilt of power poles. Background Technology

[0002] As a crucial load-bearing structure in power transmission networks, the demolding and hoisting stages of power poles during manufacturing are critical periods where their posture is most susceptible to unexpected changes, potentially leading to pole damage or safety accidents. Traditional methods for detecting the tilt of power poles primarily rely on visual observation and experience-based judgment by on-site personnel, supplemented by bubble levels for static or quasi-static tilt checks.

[0003] However, traditional methods struggle to achieve real-time, continuous, and accurate monitoring of tilt angles during continuous, dynamic demolding and hoisting operations. In multi-point hoisting scenarios, local tilt may differ between points, and flexural deformation may occur between adjacent points due to variations in sling tension, lifting speed, or insufficient pole stiffness. Existing technologies struggle to accurately assess the overall posture, let alone effectively identify and quantify dangerous localized excessive bending or torsion. In the initial demolding stage, the pole is partially constrained by the mold and partially lifted by the lifting equipment, making it more susceptible to irregular tilting and unexpected deformation under the combined effects of lifting force, gravity, and mold constraint. If dynamic tilt detection methods cannot comprehensively consider the complex geometry of the power pole, the special hoisting process, and the complex forces involved in demolding, they cannot provide accurate, reliable, and comprehensive posture information. This makes it impossible to accurately detect the tilt of the power pole. If this complex tilt and deformation coupling state is not detected in a timely and accurate manner, it may cause the pole to scrape against the edge of the mold, or the bending stress in the middle of the pole to exceed the material limit, resulting in cracks, affecting product quality, or even causing the pole to fall or the hoisting equipment to overturn due to instability during hoisting, affecting the safety of hoisting operations. Summary of the Invention

[0004] The purpose of this invention is to provide a method and system for detecting the tilt of power poles, which solves the problem that existing technologies cannot accurately detect the tilt of power poles, making it difficult to avoid damage to the pole structure and ensuring the safety of hoisting operations.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: a method for detecting the tilt of power poles, comprising:

[0006] Acquire the tilt parameters of each suspension point collected by the tilt sensor installed on each suspension point on the power pole, and the tilt angle of each pole measured by the tilt sensor installed on the pole between two adjacent suspension points;

[0007] Based on the tilt parameter of each of the aforementioned lifting points, each differential tilt parameter is confirmed;

[0008] Based on the tilt angle of each of the aforementioned benchmarks, each spatial attitude parameter is determined;

[0009] Each differential tilt parameter and each spatial attitude parameter is compared with its corresponding preset warning threshold and preset alarm threshold to obtain the comparison results of each differential tilt and each spatial attitude.

[0010] The comparison results of each differential tilt and the comparison results of each spatial attitude are processed to obtain the pole tilt detection results.

[0011] Furthermore, this application also proposes, after obtaining the tilt parameters of each suspension point collected by the tilt sensor installed on the power pole and the tilt angle of each pole measured by the tilt sensor installed on the pole between two adjacent suspension points, a step of verifying the stability of the pole connection is also included, the steps of which include:

[0012] Obtain the connection status parameters between the benchmark and its connected suspension point;

[0013] By comparing the connection status parameters with the preset status parameters, a connection status confirmation result is obtained;

[0014] Based on the connection status confirmation result, the stability of the benchmark connection is verified, and the result of the benchmark connection status is obtained.

[0015] Furthermore, this application also proposes, before the steps of acquiring the tilt parameters of each suspension point collected by the tilt sensor installed on each suspension point of the power pole and the tilt angle of each pole measured by the tilt sensor installed on the pole between two adjacent suspension points, a step of verifying whether the acquisition of the tilt parameters of each suspension point and the tilt angle of each pole is accurate is included. The steps include:

[0016] Acquire the emitted light intensity of each light from the tilt sensor at each suspension point on the power pole and the tilt sensor on the marker pole;

[0017] Based on each emitted light intensity and intensity threshold, a comparison result of the emitted light intensity is obtained;

[0018] Based on the comparison results of the emitted light intensity, the accuracy of the obtained tilt parameters of each suspension point and tilt angle of each pole is verified, and accurate results are obtained.

[0019] Furthermore, this application also proposes a step for obtaining the tilt parameters of each suspension point collected by the tilt sensor installed on the utility pole, including:

[0020] Acquire the tilt parameters of each suspension point, including the tilt angle difference and the rate of change of the difference, collected by the tilt sensor installed on each suspension point on the power pole.

[0021] Furthermore, this application also proposes that the steps for obtaining the preset early warning threshold and the preset alarm threshold include:

[0022] Obtain the inherent attribute parameters of the power pole and the operational stage characteristics of the hoisting operation;

[0023] Based on the inherent attribute parameters of the power pole and the operational phase characteristics of the hoisting operation, preset early warning thresholds and preset alarm thresholds are determined.

[0024] Furthermore, this application also proposes that the steps for determining the preset early warning threshold and preset alarm threshold based on the inherent attribute parameters of the power pole and the operational stage characteristics of the hoisting operation include:

[0025] Based on the inherent attribute parameters of the power pole and the operational stage characteristics of the hoisting operation, a combination of parameters and characteristics data is formed;

[0026] Based on the combined data, the nonlinear characteristic parameters of the pole deformation sensitivity were confirmed;

[0027] Based on the nonlinear characteristic parameters of the power pole deformation sensitivity, a preset early warning threshold and a preset alarm threshold are determined.

[0028] Furthermore, this application also proposes a step for confirming the nonlinear characteristic parameters of the pole deformation sensitivity based on the combined data, including:

[0029] Based on the combined data, each dynamic influencing factor related to the nonlinear characteristics of the pole deformation sensitivity corresponding to the combined data is identified, including the time cumulative effect during the hoisting operation or the change of environmental conditions.

[0030] Based on the combined data and each dynamic influence factor, the nonlinear characteristic parameters of the pole deformation sensitivity were identified.

[0031] Furthermore, this application also proposes a step for confirming the nonlinear characteristic parameters of the pole deformation sensitivity based on the combined data and each dynamic influence factor, including:

[0032] Based on each of the aforementioned dynamic influence factors, determine each influence weight parameter;

[0033] Based on each of the aforementioned dynamic impact factors, a comprehensive impact assessment value is obtained;

[0034] Based on the combined data and comprehensive impact assessment values, the nonlinear characteristic parameters of the power pole deformation sensitivity were confirmed.

[0035] Furthermore, this application also proposes a step for obtaining a comprehensive impact assessment value based on each of the aforementioned dynamic impact factors, including:

[0036] Based on each of the dynamic influence factors, the current state value of each dynamic influence factor and the influence weight parameter corresponding to each dynamic influence factor are determined.

[0037] Identify factor combinations that exhibit coupling effects among all the dynamic influencing factors, and confirm the current state value of the identified factor combinations;

[0038] Based on the current state value in the identified combination of factors, a coupling correction value characterizing the combined effect of the coupling is determined;

[0039] The comprehensive impact assessment value is obtained based on each current state value, each impact weight parameter, and the coupling correction value.

[0040] This application also proposes a pole tilt detection system, which includes:

[0041] The acquisition module is used to acquire the tilt parameters of each suspension point collected by the tilt sensor installed on the power pole and the tilt angle of each pole measured by the tilt sensor installed on the pole between two adjacent suspension points.

[0042] The first determining module is used to confirm each differential tilt parameter based on the tilt parameter of each of the lifting points;

[0043] The second determining module is used to determine each spatial attitude parameter based on the tilt angle of each of the aforementioned benchmarks;

[0044] The comparison module is used to compare each differential tilt parameter and each spatial attitude parameter with its corresponding preset warning threshold and preset alarm threshold, respectively, to obtain the comparison results of each differential tilt and each spatial attitude.

[0045] The detection module is used to detect and process the comparison results of each differential tilt and the comparison results of each spatial attitude to obtain the pole tilt detection results.

[0046] Compared with the prior art, the pole tilt detection method and system of the present invention have the following advantages:

[0047] This invention achieves comprehensive acquisition of local and overall tilt information of power poles by acquiring tilt sensor data installed at each lifting point and on markers between adjacent lifting points. By obtaining each differential tilt parameter, the relative motion differences of each lifting point during lifting or movement are quantified, thereby assessing the coordination of multiple lifting points. Simultaneously, based on each spatial attitude parameter, the degree of bending or torsion of the pole between adjacent lifting points is directly reflected. The differential tilt parameters and spatial attitude parameters are compared with preset warning thresholds and alarm thresholds, respectively. This allows for timely identification of local relative tilt or overall deformation trends exceeding safe limits, thus obtaining the tilt detection results of the power pole. By simultaneously monitoring and analyzing the relative differences between each lifting point and the overall attitude of the pole segment, the true state of the power pole during complex dynamic lifting processes can be captured more accurately. Especially for long or variable cross-section power poles with a certain degree of flexibility, it can effectively distinguish between overall tilt and local deformation, resulting in more accurate detection. Attached Figure Description

[0048] To more clearly illustrate the specific embodiments of the present invention, the accompanying drawings used in the specific embodiments will be briefly described below. In all the drawings, the elements or parts are not necessarily drawn to scale.

[0049] Figure 1 This is a flowchart of a method for detecting the tilt of a power pole according to the present invention.

[0050] Figure 2 This is a structural block diagram of a power pole tilt detection system according to the present invention.

[0051] In the diagram: 210, Acquisition module; 220, First determination module; 230, Second determination module; 240, Comparison module; 250, Detection module.

[0052] The implementation and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0053] The following drawings disclose several embodiments of the present invention. For clarity, many practical details will be described in the following description. However, it should be understood that these practical details are not intended to limit the invention. That is, in some embodiments of the invention, these practical details are not essential. Furthermore, for the sake of simplicity, some conventional structures and components will be shown in the drawings in a simple schematic manner.

[0054] It should be noted that all directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present invention are only used to explain the relative positional relationship and movement of each component in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indication will also change accordingly.

[0055] Furthermore, in this invention, the use of terms such as "first" and "second" is for descriptive purposes only and does not specifically refer to any order or sequence, nor is it intended to limit the invention. They are merely used to distinguish components or operations described using the same technical terms, and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the technical solutions of various embodiments can be combined with each other, but only if they are feasible for those skilled in the art. If a combination of technical solutions is contradictory or impossible to implement, such a combination should be considered nonexistent and not within the scope of protection claimed by this invention.

[0056] Traditional methods of demolding and hoisting utility poles, especially for long, heavy, or variable-section poles with a degree of flexibility, often suffer from challenges when using multi-point hoisting techniques. This is because achieving perfect synchronization and ideal coordination among the multiple hoisting points in terms of lifting speed, force distribution, and spatial positioning is difficult. Relying on on-site personnel's visual observation, experience-based judgment, or static or quasi-static tilt checks using bubble levels makes it difficult to achieve real-time, continuous, and accurate monitoring of the tilt angle, particularly in complex situations. For example, consider the demolding and dual-point hoisting of a 30-meter-long, over 10-ton prestressed concrete conical utility pole using a gantry crane in a production workshop. The pole's diameter varies along its length, resulting in uneven mass distribution. The two hoisting points are located at predetermined positions near the thicker and thinner ends of the pole. During hoisting, due to the adhesive force of the mold on the lower part of the pole and slight differences in the lifting speed of the two points, the hoisting point near the thinner end may lift before the one near the thicker end, or the two points may experience uneven force distribution. Existing detection methods only reflect localized tilting at the thicker end of the rod, while the thinner end may have already significantly tilted upwards or laterally. Simultaneously, the middle section of the rod may bend due to uneven stress at both ends. The overall posture and localized deformation of the rod are already in a dangerous state. Failure to detect this complex coupling of tilting and deformation in a timely and accurate manner could lead to the rod scraping against the mold edge, or the bending stress in the middle section exceeding the material limit, causing cracks, affecting product quality, or even causing the rod to fall or the lifting equipment to overturn due to instability during hoisting.

[0057] To further understand the content, features, and effects of this invention, the following embodiments are provided, and detailed descriptions are given below in conjunction with the accompanying drawings:

[0058] Please see Figure 1 This invention provides a method for detecting the tilt of power poles, comprising the following steps:

[0059] S100: Acquire the tilt parameters of each lifting point collected by the tilt sensor installed on each lifting point of the power pole, and the tilt angle of each marker pole measured by the tilt sensor installed on the marker pole between two adjacent lifting points. Specifically, the lifting point tilt sensor is a sensor used to measure the tilt angle of its installation point relative to the direction of gravity. It is implemented using a microelectromechanical system (MEMS) tilt sensor, an electrolyte tilt sensor, or a capacitive tilt sensor, and is used to acquire local tilt information of the power pole at each lifting point during the lifting process. Simultaneously, the lifting point tilt parameters refer to the data reflecting the tilt state of the lifting point collected by the lifting point tilt sensor, including the tilt angle, tilt direction, and rate of change of the tilt angle, used to characterize the specific tilt of the power pole at each lifting point. The marker pole is a structural component connecting two adjacent lifting points on the power pole, on which tilt sensors are installed to provide a reference for measuring the relative attitude between the two adjacent lifting points. The tilt sensor is a sensor installed on the marker pole to measure the tilt angle of the marker pole itself relative to the direction of gravity. It adopts a similar type to the lifting point tilt sensor and is used to acquire the spatial attitude information of the line connecting adjacent lifting points. The tilt angle of a marker refers to the data collected by the tilt sensor on the marker that reflects the tilt state of the marker, including the tilt angle of the marker relative to the horizontal and vertical planes, and is used to characterize the spatial posture of the line connecting adjacent suspension points.

[0060] S200. Based on the tilt parameter of each lifting point, confirm each differential tilt parameter. In this embodiment, the differential tilt parameter refers to the data reflecting the relative tilt difference between two adjacent lifting points, calculated based on the tilt parameter of each lifting point. It is implemented by calculating the difference in tilt angle between adjacent lifting points and is used to evaluate the coordination status between various lifting points in a multi-lifting-point lifting system.

[0061] S300. Based on the tilt angle of each of the aforementioned poles, confirm each spatial attitude parameter. The spatial attitude parameter refers to data calculated based on the tilt angle of each pole, reflecting the attitude of the line connecting adjacent suspension points in three-dimensional space. This data is obtained by calculating the pole relative to a reference coordinate system and is used to characterize the overall bending or torsional trend of the power pole between adjacent suspension points.

[0062] S400. Compare each differential tilt parameter and each spatial attitude parameter with their corresponding preset warning threshold and preset alarm threshold, respectively, to obtain the comparison results for each differential tilt and each spatial attitude. The preset alarm threshold is a preset value used to determine whether the tilt state has reached a dangerous range, and is used to trigger an alarm when a danger occurs.

[0063] S500: The comparison results of each differential tilt and the comparison results of each spatial attitude are processed to obtain the pole tilt detection results. By combining the differential tilt parameters reflecting the local relative tilt of each lifting point with the benchmark spatial attitude parameters reflecting the overall attitude between adjacent lifting points, the complex tilt and deformation state of the pole during multi-point lifting is comprehensively evaluated, achieving the effect of timely detection of coordination failure and excessive deformation, improving lifting safety and product quality.

[0064] This application achieves comprehensive acquisition of local and overall tilt status information of power poles by obtaining tilt sensor data installed on each suspension point of the power pole and on the marker between two adjacent suspension points. Based on the acquired suspension point tilt parameters, differential tilt parameters between each suspension point are calculated to quantify the relative motion differences of each suspension point during lifting or movement, thereby assessing the coordination of multiple suspension points. Simultaneously, based on the acquired marker tilt angles, spatial attitude parameters of each marker are calculated, directly reflecting the degree of bending or torsion of the pole between two adjacent suspension points. Subsequently, the differential tilt parameters and spatial attitude parameters are compared with preset warning thresholds and alarm thresholds, respectively. Local relative tilt or overall deformation trends exceeding the safe range are promptly identified; finally, the tilt detection results of the power pole are obtained. By simultaneously monitoring and analyzing the relative differences between lifting points and the overall posture of the pole segment, the true state of the power pole during complex dynamic lifting processes can be captured more accurately. Especially for long or variable cross-section power poles with a certain degree of flexibility, it can effectively distinguish between overall tilt and local deformation, avoiding misjudgment or omission, thereby improving the accuracy of power pole tilt detection. It can issue early warnings or alarms in a timely manner, guiding operators to make adjustments or suspend operations, thus avoiding structural damage to the power pole, improving product quality, and ensuring the safety of lifting operations.

[0065] Based on the above embodiments, this application further proposes, after obtaining the tilt parameters of each suspension point collected by the tilt sensor installed on the power pole and the tilt angle of each pole measured by the tilt sensor installed on the pole between two adjacent suspension points, a step of verifying whether the pole connection is stable is also included. The steps include:

[0066] Obtain the connection status parameters between the marker and its connected suspension points. These connection status parameters are physical quantities that characterize the tightness or integrity of the connection between the marker and its connected suspension points. They are obtained using measuring devices such as stress sensors, displacement sensors, vibration sensors, or acceleration sensors, and are used to quantify the current state of the connection.

[0067] By comparing the connection status parameters with the preset status parameters, a connection status confirmation result is obtained. The preset status parameters refer to standard values ​​or ranges used to determine whether the connection between the marker and the suspension point is in a normal and stable state. These parameters are determined through theoretical calculations or experimental tests based on factors such as the structural characteristics, material properties, installation process, and actual usage environment of the marker and suspension point, and serve as a reference benchmark for evaluating the connection status parameters.

[0068] Based on the connection status confirmation result, the stability of the pole connection is verified, and the result of the pole connection status is obtained. Specifically, if the pole connection is verified to be stable, a stable connection result is obtained; conversely, if the pole connection is verified to be unstable, an unstable connection result is obtained. This effectively identifies and eliminates data errors caused by unstable pole connections during power pole tilt detection, improving the reliability of spatial attitude parameters based on the pole tilt angle. This, in turn, enhances the accuracy and reliability of the entire power pole tilt detection method, avoiding misjudgments or omissions caused by erroneous data, and ensuring the safety of power pole hoisting operations.

[0069] In this embodiment, by adding a step to verify the stability of the pole connection after obtaining the suspension point tilt parameters and the pole tilt angle, the accuracy and reliability of the pole tilt detection are improved. Before using the pole tilt angle to evaluate the pole attitude, the connection status between the pole and the suspension point is first checked. By obtaining the connection status parameters and comparing them with preset status parameters, it is determined whether the connection is within the normal range. Based on this judgment result, it can be confirmed whether the pole connection is stable. If the connection is unstable, it indicates that the pole tilt angle data is unreliable. At this time, the data can be corrected, discarded, or a warning can be triggered to avoid using incorrect data for subsequent tilt detection processing. Because the verification step of the pole connection stability is added, the subsequent confirmation of spatial attitude parameters based on the pole tilt angle and the joint detection processing with differential tilt parameters can be based on more reliable data, effectively eliminating the error source introduced by the pole connection problem, thus making the final pole tilt detection result more accurate and able to more realistically reflect the actual tilt state of the pole.

[0070] Based on the above embodiments, this application further proposes, before the steps of obtaining the tilt parameters of each suspension point collected by the tilt sensor installed on each suspension point of the power pole and the tilt angle of each pole measured by the tilt sensor installed on the pole between two adjacent suspension points, a step of verifying whether the acquisition of each suspension point tilt parameter and each pole tilt angle is accurate is included. The steps include:

[0071] The emitted light intensity of each tilt sensor at each suspension point on the power pole and the tilt sensor on the marker pole is acquired. The emitted light intensity refers to the intensity of the light signal emitted by the tilt sensor during operation. This intensity reflects the state of the sensor's internal light source and optical path, and is used to indirectly assess the reliability of its output data by monitoring the sensor's own operating state.

[0072] Based on each emitted light intensity and intensity threshold, a comparison result of the emitted light intensity is obtained. The intensity threshold is a preset reference value used to determine whether the emitted light intensity is normal. It can be determined based on factors such as sensor type, operating environment, and calibration standards, providing a quantitative standard to distinguish between normal and abnormal sensor operating states.

[0073] Based on the comparison results of the emitted light intensity, the accuracy of the obtained tilt parameters of each suspension point and tilt angle of each marker is verified, yielding accurate results. Specifically, the comparison result refers to the judgment result obtained by comparing the obtained emitted light intensity with an intensity threshold, such as higher than the threshold, lower than the threshold, or equal to the threshold, in order to identify sensors with abnormal emitted light intensity. The accurate result refers to the judgment conclusion on the accuracy of the tilt parameters of each suspension point and tilt angle of each marker based on the comparison results of emitted light intensity, in order to provide verified and reliable data for subsequent tilt detection.

[0074] In this embodiment, firstly, communication is established with tilt sensors installed at each suspension point on the utility pole and on the pole itself, for example via wired or wireless means, to read the sensor's internal registers or acquire its emitted light intensity data through specific instructions. These sensors can be tilt sensors based on infrared or laser technology, and their emitted light intensity can be output through internal monitoring circuitry. Then, each acquired emitted light intensity is compared with a preset intensity threshold in the system. A minimum intensity threshold can be set; if the sensor's emitted light intensity is below this threshold, it is considered abnormal. Based on this comparison result, an emitted light intensity comparison result can be obtained, such as a Boolean value or status code, indicating the operating status of each sensor. Finally, based on the emitted light intensity comparison result, the accuracy of the acquired tilt parameters at each suspension point and the tilt angle of each pole is verified. For example, if the emitted light intensity of a sensor is judged to be abnormal, the tilt parameters or angle acquired by that sensor are considered potentially inaccurate, and it is marked as unreliable data. An accurate result is obtained, which can be a list or flag indicating which data is reliable and which is unreliable. Subsequent tilt detection processing will prioritize using the data marked as reliable. By adding a data accuracy verification step before acquiring the tilt parameters of the suspension point and the tilt angle of the pole, the problem of potentially inaccurate sensor data is effectively solved. Specifically, the emitted light intensity of each tilt sensor is first acquired, which directly reflects the sensor's internal operating state. Then, the acquired emitted light intensity is compared with a preset intensity threshold to obtain a comparison result. This comparison result indicates whether there are any abnormalities in the sensor, such as light source aging or optical path obstruction. It is precisely because sensors with abnormal emitted light intensity can be identified that the accuracy of the corresponding suspension point tilt parameters and pole tilt angle can be verified based on the comparison result, and accurate results can be obtained. If the verification result shows inaccurate data, corresponding processing measures can be taken, such as marking it as invalid data, performing data correction, or triggering re-acquisition. In this way, the data input to subsequent tilt detection steps (such as confirming differential tilt parameters and spatial attitude parameters based on parameters, and performing comparison and detection processing) is reliable, thereby improving the reliability and accuracy of power pole tilt detection results and avoiding misjudgments caused by using incorrect data.

[0075] Based on the above embodiments, this application also proposes a step for obtaining the tilt parameters of each suspension point collected by the tilt sensor installed on the power pole, including:

[0076] The system acquires tilt parameters for each suspension point on the power pole, including the tilt angle difference and the rate of change of the difference, collected by tilt sensors installed at each suspension point. In this embodiment, the suspension point tilt parameters refer to the data set used to describe the tilt state at the suspension point of the power pole. The tilt angle difference refers to the difference between the tilt angle of the suspension point at the current moment and the tilt angle at the previous reference moment. The rate of change of the difference refers to how quickly the tilt angle difference changes over time.

[0077] In this embodiment, when acquiring the tilt parameters of each suspension point mounted on the power pole using tilt sensors, instead of simply acquiring the tilt angle, the system acquires tilt parameters including the tilt angle difference and the rate of change of that difference. These parameters are used for subsequent differential tilt parameter verification, comparison with thresholds, and final detection processing. By introducing the rate of change of the difference, potential rapid tilt risks can be identified earlier and more accurately, even if the current tilt angle difference is within a small range. This more refined parameter acquisition method makes subsequent differential tilt analysis and overall detection more sensitive and reliable, solving the problem that tilt angle alone cannot comprehensively assess the tilt state. Combined with subsequent detection steps, this approach allows the entire detection method to make judgments based on richer and more dynamic information, thereby improving the accuracy and reliability of power pole tilt detection.

[0078] Based on the above embodiments, this application also proposes a step for obtaining the preset early warning threshold and the preset alarm threshold, including:

[0079] The inherent property parameters of the power pole and the operational stage characteristics of the hoisting operation are obtained. The inherent property parameters refer to the characteristic data related to the structure and materials of the power pole itself, characterized by information including but not limited to the material type, length, cross-sectional shape, and wall thickness, reflecting the deformation sensitivity of the power pole under stress. The operational stage characteristics of the hoisting operation refer to the specific state of the power pole during the entire hoisting process, characterized by information including but not limited to the demolding stage, lifting stage, transportation stage, and positioning stage, reflecting the stress patterns and risk levels that the power pole may face in different operational stages.

[0080] Based on the inherent attribute parameters of the power pole and the characteristics of the lifting operation phase, preset warning thresholds and preset alarm thresholds are determined. Specifically, determining the preset warning thresholds and preset alarm thresholds involves calculating or finding the applicable tilt warning and alarm limits for the current power pole and the current operation phase based on the input parameters and characteristics. This can be achieved through calculations using, but is not limited to, existing data models, to provide a dynamically adjusted reference standard for subsequent tilt status assessments.

[0081] Specifically, the system first scans the QR code on the power pole or retrieves its associated inherent attribute parameters from the production management system. These parameters include information such as whether it is a prestressed concrete tapered pole, 25 meters in length, and 300 millimeters in tip diameter. Simultaneously, operators can select the current hoisting operation stage on the control interface, such as the "demolding stage," or the system can automatically identify the operation stage by detecting the separation of the hoisting equipment from the mold using sensors. Then, the system queries or calculates within a pre-established database or model based on the acquired inherent attribute parameters of the power pole and the characteristics of the operation stage. For example, the database stores recommended threshold ranges for different types of power poles at different operation stages, or a model trained on historical data can predict appropriate thresholds based on input parameters and features. Based on the query or calculation results, the system determines the preset warning threshold and preset alarm threshold required for the current operation. For instance, for this 25-meter tapered pole in the demolding stage, the warning threshold might be set at a certain angle value, and the alarm threshold at a larger angle value. These dynamically determined thresholds were then compared with real-time acquired differential tilt parameters and spatial attitude parameters to determine whether the tilt of the power pole exceeded the safe range.

[0082] In this embodiment, by acquiring the inherent property parameters of the power pole and the operational stage characteristics of the hoisting operation, and determining preset warning thresholds and preset alarm thresholds based on these parameters and characteristics, the aforementioned problems can be solved. This is because the inherent property parameters of the power pole are directly related to its structural stiffness and deformation characteristics; power poles of different materials, lengths, or cross-sectional shapes will produce different tilting and deformation responses under the same force. Simultaneously, the operational stage characteristics of the hoisting operation reflect the changes in force boundary conditions and risks during the operation; for example, the force patterns during the demolding stage are drastically different from those during the aerial transport stage. It is precisely because these key factors affecting the tilt state are fully considered that the preset warning thresholds and alarm thresholds can be dynamically adjusted according to the actual situation, thereby more accurately reflecting the true tilt risk of the power pole at the current operational stage. This dynamic threshold setting, combined with the step in the basic scheme that compares differential tilt parameters and spatial attitude parameters, makes tilt detection no longer dependent on fixed, universal thresholds, but adaptable to different types of power poles and the characteristics of different operational stages. This improves the accuracy and reliability of the judgment, effectively avoiding false alarms or missed alarms caused by threshold mismatch, thereby enhancing the effectiveness of the entire power pole tilt detection method.

[0083] Based on the above embodiments, this application also proposes the following steps for determining the preset early warning threshold and preset alarm threshold based on the inherent attribute parameters of the power pole and the operational stage characteristics of the hoisting operation:

[0084] Based on the inherent property parameters of the power pole and the operational stage characteristics of the hoisting operation, a combination of parameter and feature data is formed. This combination of parameter and feature data refers to a data set or structure formed by integrating the inherent property parameters of the power pole (e.g., material, cross-sectional shape, length, and weight distribution) with the operational stage characteristics of the hoisting operation (e.g., current hoisting speed, lifting angle, stress distribution at the lifting points, and ambient temperature). It is implemented using vectors, matrices, structures, or database records, aiming to gather multiple factors affecting power pole deformation and provide comprehensive input for subsequent analysis.

[0085] Based on the combined data, nonlinear characteristic parameters of the power pole's deformation sensitivity were identified. Specifically, nonlinear characteristic parameters refer to parameters that characterize the nonlinear relationship between the power pole's deformation response and the load or attitude change when subjected to external loads or attitude changes. For example, in certain critical states or near load thresholds, small load changes may lead to significant nonlinear growth in deformation. These parameters can quantify the degree of nonlinearity, inflection point location, or rate of change. They can be implemented using coefficients of nonlinear models, parameters of piecewise functions, or specific indices extracted from experimental data or simulation results. The aim is to capture the true deformation law of the power pole under complex stress or attitude conditions, overcoming the limitations of linear models in accurately describing the deformation.

[0086] Based on the nonlinear characteristic parameters of the power pole deformation sensitivity, a preset early warning threshold and a preset alarm threshold are determined.

[0087] Specifically, the steps for determining the preset warning threshold and preset alarm threshold can be implemented as follows: First, collect the specific inherent attribute parameters of the power pole to be hoisted, such as its model, material grade, actual measured length, diameter or size of each section, and mass distribution data obtained from design drawings or actual measurements. Simultaneously, acquire the real-time operational stage characteristics of the current hoisting operation, such as the current lifting speed, the relative height difference between the main and auxiliary lifting points, the angle between the sling and the pole, and the ambient temperature obtained through sensors or the control system. Integrate these collected inherent attribute parameters and operational stage characteristics into a structured dataset, forming a combination of parameters and features. Next, based on this combined data, confirm the nonlinear characteristic parameters of the power pole's deformation sensitivity by consulting a pre-established nonlinear deformation model or lookup table. This model or lookup table can be trained based on a large amount of experimental data, finite element simulation analysis, or historical hoisting data. It can output key parameters characterizing the degree of nonlinearity of the power pole's deformation under the current state, such as a nonlinear amplification factor, a critical angle value, or a time-related cumulative deformation factor, based on the input combined data. Finally, based on the confirmed nonlinear characteristic parameters of the power pole deformation sensitivity, combined with the basic linear threshold, the final preset warning threshold and preset alarm threshold are determined by a calculation formula or another lookup table. For example, if the nonlinear characteristic parameters show that the deformation sensitivity is high in the current state, a correction coefficient of less than 1 can be multiplied by the basic threshold, or a more conservative threshold can be obtained directly from a multidimensional lookup table that takes nonlinearity into account.

[0088] In this embodiment, combined data of parameters and characteristics are formed based on the inherent property parameters of the power pole and the operational stage characteristics of the hoisting operation. This comprehensively considers multiple factors affecting the deformation of the power pole. The reason for forming combined data is that the deformation sensitivity of the power pole is not determined by a single factor, but is the result of the interaction of multiple factors. For example, power poles of the same material may exhibit significantly different deformation behaviors under different hoisting angles or speeds, and vice versa. Because of the combined data containing multiple factors, this application can identify the nonlinear characteristic parameters of the power pole's deformation sensitivity. The reason for identifying these nonlinear characteristic parameters is that nonlinear relationships are often hidden in the complex interactions of multiple factors. By analyzing the combined data, it is possible to reveal how these factors collectively affect the nonlinear characteristics of the power pole. Deformation behavior, for example, through data analysis or model identification, can reveal that when certain inherent properties are combined with characteristics of specific operational stages, the deformation sensitivity of power poles exhibits a nonlinear, abrupt, or accelerating trend. Because of the confirmed nonlinear characteristic parameters of power pole deformation sensitivity, this application can determine preset warning thresholds and preset alarm thresholds based on these parameters. The reason for determining thresholds based on nonlinear characteristic parameters is that traditional threshold setting methods based on linear assumptions cannot accurately reflect the true risk of power poles in nonlinear regions. By incorporating nonlinear characteristic parameters into the threshold determination process, the threshold setting can better align with the actual deformation patterns of power poles. For example, in regions where deformation sensitivity increases nonlinearly, the threshold can be appropriately lowered, thereby issuing warnings or alarms earlier and preventing excessive deformation. Through the synergistic effect of the above steps, this application can more accurately predict the deformation risk of power poles, thus setting more accurate and reliable warning and alarm thresholds. Compared to simple threshold setting based solely on inherent properties and operational stage characteristics, this approach more effectively addresses the nonlinear problem of deformation sensitivity during power pole hoisting.

[0089] Based on the above embodiments, this application also proposes a step for confirming the nonlinear characteristic parameters of the deformation sensitivity of power poles based on the combined data, including:

[0090] Based on the combined data, each dynamic influencing factor related to the nonlinear characteristics of the pole deformation sensitivity corresponding to the combined data is identified, including the time cumulative effect during the hoisting operation or changes in environmental conditions. These dynamic influencing factors refer to factors that affect the pole deformation sensitivity over time or due to changes in the external environment during the pole hoisting operation, including changes in ambient temperature, humidity, wind force, light intensity, hoisting speed, changes in the stress distribution of the slings over time, and the creep effect of the pole material under continuous stress. Specifically, identifying each dynamic influencing factor corresponding to the combined data means identifying specific dynamic factors that may significantly affect the pole deformation sensitivity under the current working conditions, based on the specific inherent properties of the pole and the current stage of the hoisting operation. The purpose is to specifically consider the impact of the actual working environment and process on the pole deformation characteristics.

[0091] Based on the combined data and each dynamic influencing factor, the nonlinear characteristic parameters of the pole deformation sensitivity are identified. Specifically, identifying the nonlinear characteristic parameters of the pole deformation sensitivity based on the combined data and each dynamic influencing factor means comprehensively considering the static properties of the pole, the characteristics of the operation stage, and the identified dynamic influencing factors. This is done through methods such as model fitting or table lookup to determine specific parameter values ​​describing the nonlinear relationship of the pole deformation sensitivity, thereby obtaining more accurate nonlinear characteristic parameters that are closer to actual working conditions. Specifically, when combining data based on the pole model (inherent attribute parameter) and the current hoisting stage (operation stage characteristic), the current ambient temperature, wind speed, and elapsed time since hoisting can be simultaneously obtained. These ambient temperature, wind speed, and elapsed time are the dynamic influencing factors corresponding to the combined data. Then, using the pole model, hoisting stage, current ambient temperature, wind speed, and elapsed time as input, a pre-trained model (e.g., a machine learning model based on historical hoisting data and environmental data) is used to obtain the nonlinear characteristic parameters of the pole's deformation sensitivity at the current hoisting stage. This model considers the deformation characteristics of different types of power poles under the influence of dynamic factors such as temperature, wind speed and duration at different lifting stages, and outputs a dynamically corrected nonlinear characteristic parameter.

[0092] In this embodiment, based on combined data formed from the inherent property parameters of the power pole and the characteristics of the hoisting operation stage, dynamic influencing factors related to the nonlinear characteristics of the power pole's deformation sensitivity are further considered, such as the time accumulation effect or changes in environmental conditions during the hoisting operation. This allows for a more accurate confirmation of the nonlinear characteristic parameters of the power pole's deformation sensitivity. Specifically, firstly, relevant dynamic influencing factors under the current working conditions are identified based on the combined data. These factors reflect real-time changes and environmental disturbances during the hoisting process. Then, these dynamic influencing factors are combined with the combined data and used as input to confirm the nonlinear characteristic parameters of the power pole's deformation sensitivity. This method overcomes the limitations of relying solely on static properties and operation stage characteristics, incorporating dynamic changes into the parameter confirmation process. This allows the obtained nonlinear characteristic parameters to more accurately reflect the deformation response of the power pole during the actual hoisting process. By comprehensively considering static and dynamic factors, the method of this application can more comprehensively understand and predict the deformation behavior of the power pole, providing a more reliable basis for subsequent tilt detection and early warning.

[0093] Based on the above embodiments, this application also proposes a step for confirming the nonlinear characteristic parameters of the deformation sensitivity of power poles based on the combined data and each dynamic influence factor, including:

[0094] Based on each of the aforementioned dynamic influencing factors, an influence weight parameter is determined for each. The influence weight parameter is a numerical value that quantifies the degree of influence of each dynamic influencing factor on the sensitivity of power pole deformation; it can be dynamically adjusted based on historical data analysis, expert experience, or real-time monitoring data.

[0095] Based on each of the aforementioned dynamic influence factors, a comprehensive impact assessment value is obtained. This comprehensive impact assessment value refers to the overall evaluation result of the current deformation sensitivity state of the power pole after comprehensively considering all dynamic influence factors and their influence weights. It can be a single value or a set of values ​​representing different aspects of the impact.

[0096] Based on the combined data and comprehensive impact assessment values, the nonlinear characteristic parameters of the power pole deformation sensitivity were identified. Specifically, the nonlinear characteristic parameters of the power pole deformation sensitivity refer to a mathematical model or set of parameters that describe the nonlinear relationship between the deformation response of the power pole and external factors under different loads, attitudes, or environmental conditions. These parameters can be a set of coefficients, a function model, or a lookup table.

[0097] Specifically, each influence weight parameter is determined based on each dynamic influence factor. By analyzing a large amount of historical hoisting data, a statistical relationship is established between dynamic influence factors (such as ambient temperature, wind speed, and hoisting duration) and the actual deformation sensitivity of the power pole. Regression analysis or machine learning algorithms are used to calculate the influence weight of each factor. A comprehensive influence assessment value is obtained based on each dynamic influence factor. The current monitoring value of each dynamic influence factor is weighted and summed with its determined influence weight parameter. For example, the comprehensive influence assessment value can be calculated as the current temperature value multiplied by the temperature weight plus the current wind speed value multiplied by the wind speed weight. Based on the combined data and the comprehensive influence assessment value, the nonlinear characteristic parameters of the power pole deformation sensitivity are confirmed. The combined data formed by the inherent attribute parameters of the power pole (such as pole type, length, cross-sectional shape, and material strength), the operational stage characteristics of the hoisting operation (such as demolding stage, lifting stage, and translation stage), and the calculated comprehensive influence assessment value are used as input. The data is then calculated through a pre-established nonlinear model (e.g., a multilayer perceptron neural network or a nonlinear regression equation) to output a set of nonlinear characteristic parameters characterizing the deformation sensitivity of the power pole. Alternatively, a multidimensional lookup table can be constructed, with the table index determined by the combined data and the comprehensive impact assessment value. The table stores the corresponding nonlinear characteristic parameters, which are then retrieved by looking up the table.

[0098] In this embodiment, the role of dynamic influencing factors is further considered when confirming the nonlinear characteristic parameters of power pole deformation sensitivity based on combined data. Specifically, firstly, for each identified dynamic influencing factor, such as the time cumulative effect or changes in environmental conditions, its influence on power pole deformation sensitivity is quantified, resulting in an influence weight parameter. This allows subsequent evaluations to distinguish the influence levels of different dynamic factors. Secondly, based on each dynamic influencing factor and its corresponding influence weight parameter, a comprehensive influence assessment value is obtained, reflecting the impact of all dynamic factors on power pole deformation sensitivity. Finally, the combined data formed by the inherent properties of the power pole and the characteristics of the operational stage are combined with this comprehensive assessment value reflecting dynamic influence to jointly confirm the nonlinear characteristic parameters of power pole deformation sensitivity. This method overcomes the limitations of relying solely on static combined data to evaluate nonlinear characteristics, and can capture the changing patterns of power pole deformation sensitivity during dynamic hoisting. The nonlinear characteristic parameters confirmed in this way can characterize the deformation response of the power pole under different working conditions, thereby providing a basis for subsequently determining warning thresholds and alarm thresholds, and thus improving the accuracy of the power pole tilt detection method.

[0099] Based on the above embodiments, this application also proposes a step for obtaining a comprehensive impact assessment value based on each of the dynamic impact factors, including:

[0100] Based on each dynamic influencing factor, the current state value of each dynamic influencing factor and the corresponding influence weight parameter are determined. The current state value refers to the specific quantitative value or level of a dynamic influencing factor at a specific moment, expressed using real-time sensor readings, environmental parameter acquisition values, or instantaneous values ​​calculated based on the model, to reflect the degree of influence of the factor at the current moment. The influence weight parameter refers to a pre-determined value reflecting the relative importance of different dynamic influencing factors on the tilt of power poles, determined using expert experience, historical data analysis, or model training, to distinguish the contribution of different factors in the comprehensive evaluation.

[0101] Identify factor combinations exhibiting coupling effects among all the dynamic influencing factors, and confirm the current state value of the identified factor combinations. Coupling effects refer to nonlinear interactions between two or more dynamic influencing factors. Factor combinations refer to a set of specific dynamic influencing factors identified as having coupling effects, identified using pre-defined rules, correlation analysis, or machine learning algorithms to focus on factor groups with significant interactions.

[0102] Based on the current state values ​​of the identified factor combinations, a coupling correction value characterizing the combined effect of the coupling is determined. The coupling correction value refers to the amount of correction used to adjust the results based on the independent factor evaluations, calculated according to the current state of the factor combinations with coupling effects. It can be determined using a lookup table method, nonlinear function calculation, or based on the predicted values ​​of the coupling model, to quantify the contribution of the coupling effect to the overall effect and correct the bias of the simple superposition model.

[0103] The comprehensive impact assessment value is obtained based on each current state value, each influence weight parameter, and the coupling correction value. The comprehensive impact assessment value refers to the final quantitative assessment result obtained by comprehensively considering the current state, influence weight, and coupling effect between each dynamic influence factor. It can be calculated by weighted summation and superimposing coupling correction terms, aiming to provide a single index that comprehensively and accurately reflects the combined impact of all current dynamic factors on the deformation sensitivity of power poles.

[0104] In this embodiment, the accuracy of the comprehensive impact assessment is improved by introducing the quantification of the coupling effects between dynamic influencing factors. Specifically, the scheme first quantifies the current state of each dynamic influencing factor and, in conjunction with preset influence weight parameters, preliminarily assesses the independent influence of each factor. Based on this, the scheme further identifies factor combinations with nonlinear correlations and obtains the current state of the factors in these combinations. Based on the current state of these coupled factor combinations, a coupling correction value characterizing their combined influence is calculated. Finally, the independent weighted influence of each factor is combined with the calculated coupling correction value to obtain the comprehensive impact assessment value. This method not only considers the individual contribution of each factor but, more importantly, captures and quantifies the interactions between factors, thus ensuring that the assessment results reflect the actual situation. It is precisely because of the accurate comprehensive impact assessment value that the nonlinear characteristic parameters of the power pole deformation sensitivity can be precisely confirmed, thereby determining preset warning thresholds and preset alarm thresholds that meet actual needs and improving the reliability of power pole tilt detection.

[0105] Based on any of the above embodiments, please refer to Figure 2 This application also proposes a pole tilt detection system, which includes an acquisition module 210, a first determination module 220, a second determination module 230, a comparison module 240, and a detection module 250.

[0106] The acquisition module 210 is used to acquire the tilt parameters of each suspension point collected by the tilt sensor installed on the power pole and the tilt angle of each pole measured by the tilt sensor installed on the pole between two adjacent suspension points.

[0107] The first determining module 220 is used to confirm each differential tilt parameter based on the tilt parameter of each of the suspension points.

[0108] The second determining module 230 is used to determine each spatial attitude parameter based on the tilt angle of each of the aforementioned benchmarks.

[0109] The comparison module 240 is used to compare each differential tilt parameter and each spatial attitude parameter with its corresponding preset warning threshold and preset alarm threshold, respectively, to obtain the comparison result of each differential tilt and the comparison result of each spatial attitude.

[0110] The detection module 250 is used to process the comparison results of each differential tilt and each spatial posture to obtain the pole tilt detection result. Through the collaborative work of the acquisition module 210, the first determination module 220, the second determination module 230, the comparison module 240, and the detection module 250, a pole tilt detection method based on lifting point tilt parameters and pole tilt angle can be realized. This system can collect tilt data at the pole's location, perform parameter analysis and threshold comparison, thereby determining the pole's tilt state, including the overall tilt trend and local deformation. This helps to promptly identify risks, provides posture monitoring information for pole demolding and hoisting operations, and improves the safety and efficiency of the operation.

[0111] This invention acquires tilt data of power pole positions via an acquisition module 210, including tilt parameters reflecting the local attitude of the suspension points and pole tilt angles reflecting the pole's shape between adjacent suspension points. This data acquisition is possible because the system is equipped with corresponding sensors, and the acquisition module 210 aggregates the data. Based on this data, the first determination module 220 can calculate differential tilt parameters based on the suspension point tilt parameters, quantifying the relative attitude differences between each suspension point; simultaneously, the second determination module 230 can calculate spatial attitude parameters based on the pole tilt angles, assessing local pole deformation. Furthermore, the comparison module 240 compares these parameters with preset thresholds, generating comparison results. Finally, the detection module 250 comprehensively analyzes these comparison results to draw detection conclusions regarding the overall and local tilt state of the power pole. This systematic data acquisition, processing, analysis, and judgment process enables this application to overcome the limitations of traditional methods that rely on a single sensor or visual observation, achieving accurate detection of power pole tilt and deformation.

[0112] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered within the scope of the present invention specification.

Claims

1. A method for detecting the tilt of power poles, characterized in that, include: Acquire the tilt parameters of each suspension point collected by the tilt sensor installed on each suspension point on the power pole, and the tilt angle of each pole measured by the tilt sensor installed on the pole between two adjacent suspension points; Based on the tilt parameter of each of the aforementioned lifting points, each differential tilt parameter is confirmed; Based on the tilt angle of each of the aforementioned benchmarks, each spatial attitude parameter is determined; Each differential tilt parameter and each spatial attitude parameter is compared with its corresponding preset warning threshold and preset alarm threshold to obtain the comparison results of each differential tilt and each spatial attitude. The comparison results of each differential tilt and the comparison results of each spatial attitude are processed to obtain the pole tilt detection results.

2. The method for detecting the tilt of a power pole according to claim 1, characterized in that, After acquiring the tilt parameters of each suspension point collected by the tilt sensor installed on the power pole and the tilt angle of each pole measured by the tilt sensor installed on the pole between two adjacent suspension points, the process also includes a step to verify the stability of the pole connection, which includes: Obtain the connection status parameters between the benchmark and its connected suspension point; By comparing the connection status parameters with the preset status parameters, a connection status confirmation result is obtained; Based on the connection status confirmation result, the stability of the benchmark connection is verified, and the result of the benchmark connection status is obtained.

3. The method for detecting the tilt of a power pole according to claim 1, characterized in that, Before acquiring the tilt parameters of each suspension point collected by the tilt sensor installed on the power pole and the tilt angle of each pole measured by the tilt sensor installed on the pole between two adjacent suspension points, the process also includes a step to verify the accuracy of the acquisition of the tilt parameters of each suspension point and the tilt angle of each pole. This step includes: Acquire the emitted light intensity of each light from the tilt sensor at each suspension point on the power pole and the tilt sensor on the marker pole; Based on each of the emitted light intensities and intensity thresholds, a comparison result of the emitted light intensities is obtained; Based on the comparison results of the emitted light intensity, the accuracy of the obtained tilt parameters of each suspension point and tilt angle of each pole is verified, and accurate results are obtained.

4. The method for detecting the tilt of a power pole according to claim 1, characterized in that, The steps for obtaining the tilt parameters of each suspension point collected by the tilt sensor installed on the utility pole include: Acquire the tilt parameters of each suspension point, including the tilt angle difference and the rate of change of the difference, collected by the tilt sensor installed on each suspension point on the power pole.

5. The method for detecting the tilt of a power pole according to claim 1, characterized in that, The steps for obtaining the preset early warning threshold and the preset alarm threshold include: Obtain the inherent attribute parameters of the power pole and the operational stage characteristics of the hoisting operation; Based on the inherent attribute parameters of the power pole and the operational phase characteristics of the hoisting operation, preset early warning thresholds and preset alarm thresholds are determined.

6. The method for detecting the tilt of a power pole according to claim 5, characterized in that, The step of determining the preset early warning threshold and preset alarm threshold based on the inherent attribute parameters of the power pole and the operational phase characteristics of the hoisting operation includes: Based on the inherent attribute parameters of the power pole and the operational stage characteristics of the hoisting operation, a combination of parameters and characteristics data is formed; Based on the combined data, the nonlinear characteristic parameters of the pole deformation sensitivity were confirmed; Based on the nonlinear characteristic parameters of the power pole deformation sensitivity, a preset early warning threshold and a preset alarm threshold are determined.

7. The method for detecting the tilt of a power pole according to claim 6, characterized in that, Based on the combined data, the steps for confirming the nonlinear characteristic parameters of the pole deformation sensitivity include: Based on the combined data, each dynamic influencing factor related to the nonlinear characteristics of the pole deformation sensitivity corresponding to the combined data is identified, including the time cumulative effect during the hoisting operation or the change of environmental conditions. Based on the combined data and each dynamic influence factor, the nonlinear characteristic parameters of the pole deformation sensitivity were identified.

8. The method for detecting the tilt of a power pole according to claim 7, characterized in that, Based on the combined data and each dynamic influence factor, the steps for confirming the nonlinear characteristic parameters of the pole deformation sensitivity include: Based on each of the aforementioned dynamic influence factors, determine each influence weight parameter; Based on each of the aforementioned dynamic impact factors, a comprehensive impact assessment value is obtained; Based on the combined data and comprehensive impact assessment values, the nonlinear characteristic parameters of the power pole deformation sensitivity were confirmed.

9. A method for detecting the tilt of a power pole according to claim 8, characterized in that, The steps for obtaining the comprehensive impact assessment value based on each of the aforementioned dynamic impact factors include: Based on each of the dynamic influence factors, the current state value of each dynamic influence factor and the influence weight parameter corresponding to each dynamic influence factor are determined. Identify factor combinations that exhibit coupling effects among all the dynamic influencing factors, and confirm the current state value of the identified factor combinations; Based on the current state value in the identified combination of factors, a coupling correction value characterizing the combined effect of the coupling is determined; The comprehensive impact assessment value is obtained based on each current state value, each impact weight parameter, and the coupling correction value.

10. A pole tilt detection system, characterized in that, The system includes: The acquisition module is used to acquire the tilt parameters of each suspension point collected by the tilt sensor installed on the power pole and the tilt angle of each pole measured by the tilt sensor installed on the pole between two adjacent suspension points. The first determining module is used to confirm each differential tilt parameter based on the tilt parameter of each of the lifting points; The second determining module is used to determine each spatial attitude parameter based on the tilt angle of each of the aforementioned benchmarks; The comparison module is used to compare each differential tilt parameter and each spatial attitude parameter with its corresponding preset warning threshold and preset alarm threshold, respectively, to obtain the comparison results of each differential tilt and each spatial attitude. The detection module is used to detect and process the comparison results of each differential tilt and the comparison results of each spatial attitude to obtain the pole tilt detection results.

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