Real-time monitoring system and method for derrick deformation and head sheave inclination based on GNSS (Global Navigation Satellite System) technology

Abstract

The invention belongs to the technical field of mine safety monitoring, and discloses a GNSS technology-based derrick deformation and head sheave inclination real-time monitoring system and method, and the system comprises a GNSS real-time monitoring station network module, a data cleaning module, a space-time analysis module, and a derrick and head sheave inclination monitoring module. The GNSS real-time monitoring station network module is used for collecting three-dimensional deformation monitoring data of the derrick in real time; the data cleaning module is used for cleaning the three-dimensional deformation monitoring data of the derrick; the space-time analysis module is used for performing visual analysis on the space-time deformation characteristics of the derrick in combination with the ground state correction model to obtain the deformation trend of the derrick; and the derrick and head sheave inclination monitoring module is used for monitoring station network configuration based on the GNSS and calculating the inclination angles of the derrick and the head sheave by using the cleaned derrick three-dimensional deformation monitoring data. According to the invention, high-precision real-time monitoring of derrick deformation and head sheave inclination is realized, and technical support is provided for safety assessment of a mining area derrick structure.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of mine safety monitoring, and particularly relates to a real-time monitoring system and method for shaft head deformation and crown pulley inclination based on GNSS technology, which is suitable for health state evaluation and safety warning of shaft head structure in the fields of mining, metallurgy and the like. BACKGROUND

[0002] As a key bearing structure of the mine hoisting system, the safety state of the shaft head plays a decisive role in the production safety and the safety of life and property of personnel in the mine area. However, in the mine operation, the shaft head is subjected to the double influences of mechanical load and environmental factors for a long time, and is extremely prone to three-dimensional cumulative deformation. If the millimeter-level displacement or the slight structural abnormality cannot be found in time, major accidents such as shaft head inclination, support structure fracture and even collapse may be caused. Therefore, the high-precision and real-time shaft head deformation monitoring technology has become an urgent demand of the mine safety management.

[0003] Traditional monitoring methods of the derrick mainly rely on ground surveying techniques such as total station and level, and the structural stability is evaluated by collecting data manually at regular intervals. However, this method has three major defects: first, it is time-consuming and the measurement cycle is long, usually in weeks or months, which is difficult to capture the dynamic deformation process and cannot meet the real-time warning requirements; second, it is high in labor cost, and frequent measurement points and manual reading are required, which is low in operation efficiency and high in risk in harsh mine environment; third, the spatial coverage is insufficient, and only discrete point data can be obtained, which is difficult to fully reflect the overall deformation trend of the derrick and the monitoring accuracy of the key nodes (such as the crown block) is insufficient. In recent years, the popularization of GNSS technology has brought new opportunities for derrick monitoring, and real-time dynamic monitoring based on satellite positioning has been gradually applied to engineering structure health assessment. However, there are still many bottlenecks in the existing schemes: the data quality is limited, the multipath effect is significant in the mine environment, and the conventional filtering method is difficult to effectively separate the true deformation and noise; the spatio-temporal analysis model is missing, and the existing research mostly uses static reference comparison method, which cannot dynamically describe the spatio-temporal evolution law of deformation, and the distinguishing ability of periodic swing and cumulative deformation is insufficient; the risk assessment is extensive, and the existing warning system mostly relies on a single threshold judgment, without considering the correlation between deformation and structure parameters, and the false alarm rate is high. In addition, the current research field also has obvious scene limitations, and the GNSS deformation monitoring technology mostly focuses on large-scale scenes such as dams, bridges and landslides, and lacks special monitoring models and methods for high-rise, locally concentrated load and complex mechanical disturbance affected structures such as mine derricks. For example, the deformation of the derrick crown block platform shows obvious directionality and spatial heterogeneity due to the frequent bearing of the transverse tension of the lifting rope, and the general model is difficult to accurately describe such characteristics. In summary, the existing technology cannot effectively solve the core problems of insufficient data accuracy, coarse spatio-temporal analysis granularity and lack of scientific risk assessment in mine derrick monitoring. The present application aims at the above-mentioned defects and proposes a GNSS monitoring system integrating data cleaning, dynamic spatio-temporal modeling and deformation and inclination calculation, which aims to improve the accuracy and efficiency of mine derrick monitoring and provide technical support for mine derrick safety. SUMMARY

[0004] To solve the problem of long monitoring period and inability to dynamically monitor and warn, the present application provides a GNSS technology-based real-time monitoring system and method for derrick deformation and crown block inclination, which realizes high-precision real-time monitoring of derrick deformation and crown block inclination and provides technical support for mine derrick structure safety evaluation.

[0005] To achieve the above-mentioned purposes, the present application provides the following solutions: A GNSS technology-based real-time monitoring system for derrick deformation and crown block inclination, comprising: a GNSS real-time monitoring station network module, a data cleaning module, a spatio-temporal analysis module, a derrick and crown block inclination monitoring module. The GNSS real-time monitoring station network module is used for collecting the three-dimensional deformation monitoring data of the derrick in real time. The data cleaning module is used for cleaning the three-dimensional deformation monitoring data of the derrick. The space-time analysis module is used for visually analyzing the space-time deformation characteristics of the derrick in combination with the ground state correction model to obtain the deformation trend of the derrick. The derrick and crown block inclination monitoring module is used for calculating the inclination angles of the derrick and the crown block based on the GNSS monitoring station network configuration and the cleaned three-dimensional deformation monitoring data of the derrick.

[0006] Preferably, the GNSS real-time monitoring station network module is composed of one GNSS reference station, eight GNSS monitoring stations and a monitoring and early warning cloud platform. Each GNSS real-time monitoring station is equipped with a GNSS receiver and a wireless communication module, the GNSS reference station is arranged at a position 1-3 km away from the GNSS monitoring stations to provide reference data, and the GNSS monitoring stations are distributed at key positions of the derrick according to a predetermined layout, wherein two upper crown block platforms are arranged at both sides of the crown block shaft, six lower crown block platforms are arranged at both sides of the lower crown block shaft and at four corner points of the lower crown block platform, the eight GNSS monitoring stations are used for monitoring the deformation of the key positions of the derrick, the GNSS monitoring stations at both sides of the crown block shaft are used for monitoring the inclination of the crown block, and the GNSS monitoring stations at the four corner points of the lower crown block platform are used for monitoring the inclination of the lower crown block platform; the monitoring and early warning cloud platform uses NRTK, RT-PPP, PPP-RTK and other technologies to monitor the derrick in real time by receiving GNSS observation data, and realizes real-time monitoring and early warning of the deformation of the derrick through integrated data management and analysis tools. Each GNSS real-time monitoring station is connected with the monitoring and early warning cloud platform through the wireless communication module to transmit data in real time, build a monitoring network, obtain derrick deformation data, and automatically collect three-dimensional coordinate data and related monitoring information of the derrick in the mining area at different times according to a preset time interval.

[0007] Preferably, the data cleaning module is composed of an outlier detection unit, an interpolation unit and a high-frequency denoising unit. The outlier detection unit is used for identifying outlier data points in the three-dimensional space based on the local outlier factor (LOF) algorithm and giving rejection. The interpolation unit is used for estimating and filling the missing or abnormal monitoring data points while retaining the real micro swing during the operation of the derrick by using the Savitzky-Golay smoothing interpolation method. The high-frequency denoising unit is used for filtering high-frequency noise by using the db4 wavelet soft threshold denoising technology to output a high-fidelity clean sequence.

[0008] Preferably, the space-time analysis module is composed of a base data unit, a correction term calculation unit, a space-time modeling unit and a deformation trend analysis unit; The base data unit is used for storing the monitoring data at the initial installation stage as base data; The correction term calculation unit is used for comparing the subsequent monitoring data with the base data, calculating the correction term of each monitoring point, and reflecting the deformation size and direction; The space-time modeling unit is used for constructing a model by using a space-time analysis algorithm, and analyzing the evolution law of the deformation in time and space; The deformation trend analysis unit is used for drawing a deformation trend graph, predicting the future deformation trend, and generating an intuitive deformation analysis report according to the correction term and the space-time model.

[0009] Preferably, the derrick and crown block inclination analysis module is composed of an inclination calculation unit; the inclination calculation unit is used for determining the inclination angle of the crown block platform and the crown block; For the crown block platform, a local coordinate system is established by taking the three-dimensional coordinate data of the four surrounding monitoring points as the origin, a plane is fitted, the inclination angle of the platform is obtained by calculating the included angle between the normal vector of the plane and the horizontal plane, and the projection of the normal vector on the horizontal plane is the inclination direction; For the crown block, the inclination angle of the crown block is calculated based on the ratio of the elevation difference and the distance between the monitoring points on both sides of the crown block shaft, and the inclination direction is determined by combining the three-dimensional coordinate data.

[0010] The application also provides a real-time monitoring method for derrick deformation and crown block inclination based on GNSS technology, which is realized by the system. By arranging one GNSS reference station and eight GNSS monitoring stations, a monitoring and early warning cloud platform is deployed, a GNSS monitoring network is formed, and derrick three-dimensional deformation monitoring data are collected in real time; The derrick three-dimensional deformation monitoring data are cleaned by using the Savitzky-Golay cubic spline interpolation, the local outlier factor LOF anomaly detection and the db4 wavelet soft threshold denoising method; The space-time deformation characteristics of the derrick are visually analyzed in combination with the base correction model, and the derrick deformation trend is revealed; Based on the GNSS monitoring station network configuration, the inclination angle of the derrick and the crown block is calculated by using the cleaned monitoring data.

[0011] Preferably, the method for cleaning the derrick three-dimensional deformation monitoring data by using the Savitzky-Golay cubic spline interpolation, the local outlier factor LOF anomaly detection and the db4 wavelet soft threshold denoising method comprises the following steps: Missing interpolation and preliminary smoothing: The derrick monitoring data 、 、 Three one-dimensional sequences are executed point by point Savitzky-Golay Filtering: In a sliding window of 2m+1=11 epochs, where m represents the window half-width, the local data is fitted with a cubic polynomial: ; The least squares fitting of the local data is the coefficient vector: ; Where, is the original observation value of the i + k th epoch in the window, i is the index of the current point to be estimated, is the Vandermonde matrix, k is the relative index in the window, p is the polynomial order, is the coefficient to be solved, is the original observation value vector in the window, and t j , the interpolation result is obtained by substituting the cubic polynomial t j ( t j ); Spatial anomaly detection: The three-dimensional increments of the same epoch are constructed into a vector , where, , and Savitzky-Golay represent the deformation increments in the X, Y, and H directions after processing, respectively. k - Neighborhood local reachable density: ; Where, is the three-dimensional deformation vector of the current center point, is any adjacent point vector in its k neighborhood , represents the Euclidean distance from the adjacent point vector to its th nearest neighbor vector, k then the = 20 points closest to ; k are composed of; Further, the LOF factor is obtained: ; When , it is determined to be a spatial outlier and is removed, and the missing position is again fitted with the same window Savitzky-Golay ​Polynomial extrapolation is used to fill in the missing data; High frequency denoising: The post-cleaning sequence is decomposed by db4 wavelet J=5 layers, and the detail coefficient adopts soft threshold value: ; Wherein, is the first j layer wavelet detail coefficient, k indicates the Euclidean distance, and MAD is the median absolute deviation of the detail coefficient, is the length of the sequence, is the threshold value; the reconstructed signal is the following final clean sequence: ; Wherein, is the number of wavelet decomposition layers; is the first layer scale function base; is the first j layer wavelet function base; is the approximation coefficient.

[0012] Preferably, the method for visualizing the space-time deformation characteristics of the derrick in combination with the ground state correction model comprises: Store the monitoring data at the initial installation as ground state data; Compare the subsequent monitoring data with the ground state data, calculate the correction term of each monitoring point, and reflect the deformation size and direction; Use space-time analysis algorithm to construct model, analyze the evolution law of deformation in time and space; According to the correction term and the space-time model, draw the deformation trend chart, predict the future deformation trend, and generate an intuitive deformation analysis report.

[0013] Preferably, based on the GNSS monitoring station network configuration, the method for calculating the inclination angle of the derrick and the crown wheel by using the post-cleaning monitoring data comprises: Derrick inclination angle calculation: ; Wherein, a , b are the parameters to be solved; Crown wheel inclination angle calculation: assuming that two GNSS monitoring stations are A and B, the distance between them is L, the elevation data of A and B are obtained from the monitoring data, which are H A and H B , respectively, the elevation difference ΔH=H A -H B of the two monitoring points is calculated; Assuming that the crown wheel shaft is originally horizontal, when it is tilted, the inclination angle θ is calculated:​θ ≈ΔH / L is based on the assumption of a small angle approximation, that is, when the tilt angle is less than a preset threshold, θ ≈tan θ =ΔH / L; If the tilt angle is greater than the preset threshold, the arctangent function is used for calculation, i.e. θ =arctan(ΔH / L).

[0014] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention enables high-precision real-time monitoring of derrick deformation and sheave tilt, solving the problems of long monitoring cycles and inability to provide dynamic monitoring and early warning in traditional methods, and providing technical support for safety assessment of derrick structures in mining areas. Attached Figure Description

[0015] To more clearly illustrate the technical solution of the present invention, the drawings used in the embodiments are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a hardware deployment structure diagram of a real-time monitoring system for derrick deformation and sheave tilt based on GNSS technology according to an embodiment of the present invention (the left side is a side view of the derrick monitoring part, and the right side is a front view). Figure 2 This is a flowchart illustrating a real-time monitoring method for derrick deformation and sheave tilt based on GNSS technology, according to an embodiment of the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0019] Example 1 like Figure 1 As shown, the present invention provides a real-time monitoring system for derrick deformation and sheave tilt based on GNSS technology, including a GNSS real-time monitoring station network module, a data cleaning module, a spatiotemporal analysis module, and a derrick and sheave tilt monitoring module.

[0020] The GNSS real-time monitoring station network module is used for arranging a plurality of GNSS monitoring stations at key positions of the mine shaft tower, deploying a monitoring and early warning cloud platform, receiving satellite signals in real time through a GNSS receiver and the like and collecting three-dimensional coordinate data and related monitoring information of the mine shaft tower, and forming a real-time monitoring station network. The data cleaning module is used for carrying out interpolation, outlier rejection and denoising and the like on the collected monitoring data, improving data quality and retaining true deformation information. The space-time analysis module is used for processing and analyzing the cleaned data by using a ground state correction model and the like, and revealing the space-time evolution law of the tower deformation. The tower and head sheave inclination monitoring module is used for calculating the inclination angle of the mine shaft tower and the head sheave, analyzing the inclination law, and discovering abnormalities in time. Further, in the present application, the GNSS real-time monitoring station network module is composed of one GNSS reference station, eight GNSS monitoring stations and a monitoring and early warning cloud platform. Each GNSS real-time monitoring station is equipped with a high-precision GNSS receiver and a wireless communication module, the GNSS reference station is arranged at a stable position 1-3 km away from the GNSS monitoring stations, is used for providing accurate reference data, and the GNSS monitoring stations are distributed at key positions of the tower according to a specific layout. Among them, there are two upper head sheave platforms located on both sides of the head sheave shaft, and six lower head sheave platforms, two of which are located on both sides of the lower head sheave shaft, and four of which are located at the four corner points of the lower head sheave platform. The eight GNSS monitoring stations are used for monitoring the deformation (surface displacement and uneven settlement) of the key positions of the tower. At the same time, the GNSS monitoring stations on both sides of the head sheave shaft are used for monitoring the inclination of the head sheave, and the GNSS monitoring stations at the four corner points of the lower head sheave platform are used for monitoring the inclination of the lower head sheave platform. The monitoring and early warning cloud platform receives GNSS observation data, adopts NRTK, RT-PPP, PPP-RTK and the like, and monitors the tower in real time. Through integrated data management and analysis tools, real-time monitoring and early warning of the tower deformation are realized. Each GNSS monitoring station is connected with the monitoring and early warning cloud platform through a wireless communication module, transmits data in real time, builds a stable and reliable monitoring network, ensures to obtain comprehensive and accurate tower deformation data, and automatically collects three-dimensional coordinate data and related monitoring information of the mine shaft tower at different times according to a preset time interval, thereby providing complete and continuous original data support for subsequent data processing and analysis.

[0021] Further, in the present application, the data cleaning module is composed of an outlier detection unit, an interpolation unit and a high-frequency denoising unit. The outlier detection unit accurately identifies outlier data points in three-dimensional space based on the local outlier factor (LOF) algorithm and gives rejection. The interpolation unit uses the Savitzky-Golay smoothing interpolation method to reasonably estimate and fill in missing or abnormal monitoring data points while retaining the true micro-swing during the operation of the derrick; then the high-frequency denoising unit uses the db4 wavelet soft threshold denoising technology to further filter out high-frequency noise and output a high-fidelity clean sequence.

[0022] Further, in the present application, the space-time analysis module is composed of a ground state data unit, a correction term calculation unit, a space-time modeling unit and a deformation trend analysis unit. The ground state data unit stores the monitoring data at the initial installation as ground state data. The correction term calculation unit compares the subsequent monitoring data with the ground state data to calculate the correction term of each monitoring point, reflecting the deformation size and direction. The space-time modeling unit uses space-time analysis algorithms to construct a model to analyze the evolution law of deformation in time and space. The deformation trend analysis unit draws a deformation trend graph based on the correction term and the space-time model, predicts the future deformation trend, and generates an intuitive deformation analysis report, providing a scientific basis for risk assessment and decision-making, and helping to understand the space-time evolution characteristics of the derrick deformation in time.

[0023] Further, in the present application, the derrick and crown block inclination analysis module is composed of an inclination calculation unit. The inclination calculation unit focuses on determining the inclination angle of the crown block platform and the crown block. For the crown block platform, by analyzing the three-dimensional coordinate data of the monitoring points around it, the most stable monitoring point is taken as the origin to establish a local coordinate system, a plane is fitted, and the inclination angle of the platform is obtained by calculating the angle between the plane normal vector and the horizontal plane. The projection of the normal vector on the horizontal plane is the inclination direction. For the crown block, the focus is on the ratio of the elevation difference and the distance of the monitoring points on both sides of the crown block shaft, and the arctangent function is used to calculate the inclination angle of the crown block, and the inclination direction is determined combined with the three-dimensional coordinate data. The inclination calculation unit integrates these data to provide accurate inclination information, which provides a key basis for subsequent risk assessment and early warning, and ensures the safe and stable operation of the derrick and the crown block.

[0024] Embodiment Two As shown in Figure 2 The present application provides a real-time monitoring method for derrick deformation and crown block inclination based on GNSS technology, which is realized by the system described in embodiment one, including the following steps: (1) GNSS real-time monitoring station network deployment The GNSS real-time monitoring network deployment takes "high-precision, real-time, and automated deformation monitoring of the derrick" as its core objective. Combining the spatial characteristics of the steel structure derrick, the electromagnetic and climatic environment of the mining area, and the need for maintenance-free operation in the later stage, it adopts an architecture of "1 base station + 8 monitoring stations". Through satellite navigation and positioning system monitoring, redundant power supply, wireless communication and high-level waterproof and lightning protection, a long-term stable all-weather monitoring network is constructed.

[0025] The base station is located on a rooftop or bedrock area with a stable foundation, open view, and no electromagnetic interference, within 1–3 km of the derrick. It uses a concrete base, and the antenna installation height meets specifications, keeping it away from strong electromagnetic sources. It is equipped with a high-precision satellite receiver supporting multiple systems and frequencies. The power supply system uses a combination of solar panels, energy storage batteries, and a controller to ensure continuous operation for several days, even during continuous cloudy or rainy weather. Communication uses a wireless data terminal module, supporting remote access to a fixed address. The chassis is made of stainless steel, with built-in surge protectors, and the grounding resistance meets specifications, providing the entire unit with a high level of protection.

[0026] A total of eight monitoring stations are deployed, arranged according to the principles of key nodes and symmetrical distribution: two monitoring stations are located on the upper sheave platform, symmetrically positioned on both sides of the sheave axis; six monitoring stations are located on the lower sheave platform, with four at the four corners and two on both sides of the sheave axis. These eight monitoring stations are used to monitor the deformation (surface displacement and uneven settlement) of key parts of the derrick. Simultaneously, four monitoring stations around the platform monitor the platform's tilt, and four monitoring stations on both sides of the sheave axis monitor the tilt of the sheave. The four monitoring stations around the platform are welded to the supporting brackets, extending half a meter outward from the derrick. The monitoring stations on both sides of the sheave are also welded to the supporting brackets and extend outward a certain distance. This reduces the impact of multipath interference on the monitoring data and accurately measures the correction value between the antenna phase center and the monitoring position on the derrick surface, facilitating subsequent data processing. The monitoring station's main unit uses a miniaturized, low-power satellite receiver, powered by mains electricity (with cables protected by flexible conduits), and a backup power source of lithium batteries. It supports low-power operation and sleep / wake-up modes, and the sampling frequency is adjustable. Encrypted data is uploaded to the monitoring and early warning cloud platform via a wireless communication module.

[0027] The monitoring and early warning cloud platform receives GNSS observation data and uses technologies such as NRTK, RT-PPP, and PPP-RTK to monitor the derrick in real time. Through integrated data management and analysis tools, it achieves real-time monitoring and early warning of derrick deformation. Each monitoring station is connected to the monitoring and early warning cloud platform through a wireless communication module to transmit data in real time, building a stable and reliable monitoring network to ensure the acquisition of comprehensive and accurate derrick deformation data. At the same time, it automatically collects three-dimensional coordinate data and related monitoring information of the mine derrick at different times according to preset time intervals, providing complete and continuous raw data support for subsequent data processing and analysis.

[0028] (2) Preprocessing of monitoring data Due to the damping pendulum characteristics of the derrick and the GNSS multipath effect, random missing data, outliers and high-frequency noise exist in the original sequence. In order to ensure the accuracy of subsequent modeling, the "smooth interpolation-LOF spatial anomaly detection-db4 wavelet soft threshold denoising" series processing strategy is used to preprocess the original data, and the specific process is as follows. Savitzky-Golay

[0029] 1) Interpolation and preliminary smoothing of missing data The monitoring data of the derrick 、 、 Three single-dimensional sequences are executed point by point Savitzky-Golay Filtering: in a sliding window with a width of 2m+1=11 epochs (m=5, indicating the window half-width), the local data is fitted with the following cubic polynomial: ; Where is the original observation value of the i + k th epoch in the window, i is the index of the current point to be estimated, k is the relative position index in the window, p is the polynomial order, is the coefficient to be solved.

[0030] The least squares fitting of local data is as follows: ; Where is the Vandermonde matrix, is the original observation value vector in the window. For any missing value epoch t j ( j , indicates the serial number of the missing point in the global time sequence), substitute t j into the cubic polynomial to get the interpolation result , for the X direction, this result can be denoted as ( t j ).

[0031] 2) Spatial anomaly detection The three-dimensional increment at the same epoch is constructed into a vector , where represents the deformation increment in the X, Y and H directions after processing, respectively, in the 11-epoch sliding window, the original Savitzky-Golay 、 、 , ​The window center value (or extrapolated value) is taken as the current result after three times of point-by-point polynomial least square fitting, and the missing points are filled synchronously. Finally, three smooth sequences of clean, continuous and true vibration signals are obtained, which are used for subsequent three-dimensional spatial anomaly detection. Then, the local density of the neighborhood k -neighborhood k =20)local reachable density: ; where, is the three-dimensional deformation vector of the current center point, is the k -neighborhood of any adjacent point vector, denotes the Euclidean distance between the adjacent point vector and its k nearest neighbor point vector, then consists of the = 20 points closest to k .

[0032] Further, the LOF factor is obtained: ; When , it is determined that the space is out of the norm and is rejected, and the missing position is filled back with the same window Savitzky-Golay polynomial extrapolation.

[0033] 3) High frequency denoising The cleaned sequence is decomposed by db4 wavelet J=5 layers, and the soft threshold value is used for the detail coefficient: ; where, is the j layer k th wavelet detail coefficient, denotes the Euclidean distance, and MAD is the median absolute deviation of the detail coefficient, is the sequence length, is the threshold value; the reconstructed signal is the following final clean sequence: ; where, is the number of wavelet decomposition layers; is the layer scale function base; is the j layer wavelet function base; is the approximation coefficient.

[0034] (3) Spatiotemporal analysis of monitoring station measurement data This system performs a three-step process analysis on the monitoring station data: first, preliminary surface modeling; then, further analysis using a ground-state correction model; and finally, on-site optimization of the receiver installation location based on the analysis results. The process is as follows: ① For the eight GNSS monitoring stations on the derrick, the aim is to visualize and analyze their three-dimensional deformation. , , In cases where the deformation data is not fully understood, preliminary modeling of the 3D deformation data needs to be considered. Based on the cleaned GNSS 3D deformation time series, a cubic spline interpolation surface model is established for the 3D deformation of the upper and lower sheaves and the lower sheave platform monitoring station using visualization software. Discrete observations are resampled into continuous surfaces. Subsequently, a cumulative deformation surface map is drawn in the same coordinate system, and the spatial undulations of each monitoring point are visually displayed using contour line color differences. Displacement and settlement are assessed based on the overall deformation undulation image. During the assessment, the deformation magnitude is first determined by the surface extrema and gradient: if the deformation is small and the gradient change is gentle, it is considered "small and uniform"; if local convexity or gradient abruptness occurs, it is delineated as an "significant settlement / lateral displacement" anomaly area. ② To better analyze the deformation patterns, for deformation data involving temporal and spatial changes, a spatiotemporal big data model is specifically considered for analysis. For each spatiotemporal model, considering cost, data redundancy, and intuitiveness, the ground state correction model is used to process the monitoring data. Based on the theory of the ground-state correction model, in analyzing the variation characteristics of monitoring station time-series data relative to a specified time, only the position information at that time and the position changes at other times relative to that specified time need to be stored. This eliminates the need to store all position information at other times. Furthermore, thanks to the freedom in selecting ground-state data points, this model allows for the selection of different starting points and the observation of the movement trajectory relative to that point over subsequent time periods, highlighting the spatiotemporal visualization of deformation monitoring. A model is established to quantitatively study the displacement of each monitoring station relative to the ground-state data (assuming no position change, and setting the first epoch of data received after equipment installation as the ground state), i.e., the correction term. The degree of derrick deformation is then visualized and analyzed based on the cohesiveness of the correction term. Finally, addressing the identified problems, the GNSS monitoring stations around the derrick's undercarriage platform and on both sides of the undercarriage were adjusted to suitable positions. The monitoring stations were extended and fixed outwards by welding T-shaped steel structure support brackets, reducing signal obstruction at the source and optimizing monitoring conditions.

[0035] (4) Monitoring the tilt of the derrick and sheave Displacement and uneven settlement of the derrick surface need to be obtained through monitoring data from the monitoring and early warning cloud platform, and the monitoring of the tilt of the derrick and sheave needs to be implemented based on this monitoring data.

[0036] 1) Derrick tilt calculation ① Select a reference point Stability Assessment: Analyze the historical data of the four monitoring stations on the crown block platform under the derrick to assess its stability. Choose a monitoring station with smaller deformation and stable data fluctuation as the reference point. For example, assume that monitoring station JC01 has the smallest deformation data fluctuation during the monitoring period and its position is relatively fixed compared to other monitoring stations, then JC01 can be selected as the reference point.

[0037] Record Initial Coordinates: Record the three-dimensional coordinates of the reference point at the start of monitoring as the baseline for subsequent deformation calculations. Assume that at the initial moment, the coordinates of the reference point are (X0, Y0, Z0). 、 、 ).

[0038] ②Calculate Relative Displacement Obtain Data: Obtain the three-dimensional coordinate data of the other three monitoring stations (JC02, JC03, JC04) during the monitoring period.

[0039] Calculate Relative Displacement: For each monitoring station, calculate its relative displacement with respect to the reference point at each monitoring time.

[0040] ; ③Establish Local Coordinate System Set Origin: Set the reference point JC01 as the origin of the local coordinate system, with coordinates (0, 0, 0).

[0041] Determine Coordinate Axis Direction: According to the structure of the derrick and the distribution of the monitoring stations, determine the X, Y, Z axis directions of the local coordinate system. For example, the X axis can point to one of the main extension directions of the derrick, the Y axis can point to another main extension direction perpendicular to the X axis, and the Z axis can be perpendicular to the X-Y plane, pointing to the zenith.

[0042] Coordinate Transformation: Transform the relative displacement data of the other three monitoring stations into the local coordinate system, i.e., the coordinates in the local coordinate system are: ; ④Fit Inclined Plane Collect Data Points: Collect the coordinate data of the three monitoring stations in the local coordinate system to form three data points.

[0043] Select Fitting Method: The least squares method can be used to fit the inclined plane. Assume that the equation of the inclined plane is: ; where a, b, and c are parameters to be solved. a 、 b 、 c .

[0044] ​Constructing equation group: according to the coordinate data of the three monitoring stations, the following equation group is constructed: ; By solving the equation group, the values of parameters a 、 b 、 c are obtained, so as to determine the equation of the inclined plane.

[0045] ⑤Calculate the inclination value Calculate the normal vector: according to the fitted inclined plane equation, the normal vector thereof is (0, 0, -1). a , b , -1).

[0046] Calculate the inclination angle: the inclination angle θ can be calculated by the angle between the normal vector and the vertical direction (Z-axis direction), and the formula is: ; The angle is the inclination angle of the sheave platform.

[0047] 2) Sheave inclination calculation The specific positions of the monitoring stations on both sides of the sheave shaft are determined to ensure that they are on the same axis of the sheave shaft and the distances from the center of the sheave shaft are equal. Assume that the two monitoring stations are A and B, and the distance between them is L. Obtain the elevation data of A and B from the monitoring data, which are H A and H B respectively. Calculate the elevation difference of the two monitoring points ΔH = H A -H B .

[0048] Assume that the sheave shaft is originally horizontal, when the inclination occurs, the inclination angle θ can be calculated by the following formula: θ ≈ΔH / L, this formula is based on the assumption of small angle approximation, that is, when the inclination angle is small, θ ≈tan θ =ΔH / L. If the inclination angle is large, the arctangent function is used for calculation, that is, θ =arctan(ΔH / L).

[0049] The above-described embodiments are only descriptions of the preferred modes of the present application, and do not limit the scope of the present application. Without departing from the design spirit of the present application, various modifications and improvements to the technical solutions of the present application made by those skilled in the art shall fall within the protection scope determined by the claims of the present application.

Claims

1. A real-time monitoring system for derrick deformation and sheave tilt based on GNSS technology, characterized in that, The system includes: a GNSS real-time monitoring station network module, a data cleaning module, a spatiotemporal analysis module, and a derrick and sheave tilt monitoring module; GNSS real-time monitoring station network module is used to collect three-dimensional deformation monitoring data of the derrick in real time; The data cleaning module is used to clean the three-dimensional deformation monitoring data of the derrick. The spatiotemporal analysis module is used to visualize and analyze the spatiotemporal deformation characteristics of the derrick by combining the ground state correction model, and to obtain the deformation trend of the derrick. The derrick and sheave tilt monitoring module is used to calculate the tilt angle of the derrick and sheave based on the GNSS monitoring station network configuration and the three-dimensional deformation monitoring data of the derrick after cleaning.

2. The system according to claim 1, characterized in that, The GNSS real-time monitoring network module consists of one GNSS reference station, eight GNSS monitoring stations, and a monitoring and early warning cloud platform. Each GNSS real-time monitoring station is equipped with a GNSS receiver and a wireless communication module. A GNSS reference station is located 1-3 km away from the GNSS monitoring stations to provide reference data. The GNSS monitoring stations are distributed according to a predetermined layout at key parts of the derrick. There are two stations on the upper sheave platform, located on both sides of the sheave axis; and six stations on the lower sheave platform, two on both sides of the lower sheave axis and four at the four corner points of the lower sheave platform. Eight GNSS monitoring stations are used to monitor deformation of key parts of the derrick. Simultaneously, the GNSS monitoring stations on both sides of the sheave axis monitor the tilt of the sheave, and the GNSS monitoring stations at the four corner points of the lower sheave platform monitor the tilt of the lower sheave platform. The monitoring and early warning cloud platform receives GNSS observation data and uses network real-time dynamic positioning (NRTK), real-time precise single-point positioning (RT-PPP), and precise single-point real-time dynamic positioning (PPP-RTK) technologies to monitor the derrick in real time. Through integrated data management and analysis tools, it achieves real-time monitoring and early warning of derrick deformation. Each GNSS real-time monitoring station connects to the monitoring and early warning cloud platform via a wireless communication module to transmit data in real time, build a monitoring network, acquire derrick deformation data, and automatically collect three-dimensional coordinate data and related monitoring information of the mine derrick at different times according to preset time intervals.

3. The system according to claim 1, characterized in that, The data cleaning module consists of an outlier detection unit, an interpolation unit, and a high-frequency noise reduction unit; The outlier detection unit is used to identify and remove outlier data points in three-dimensional space based on the Local Outlier Factor (LOF) algorithm. Interpolation unit, used to estimate and fill missing or abnormal monitoring data points while preserving the true micro-oscillations during derrick operation using Savitzky-Golay smoothing interpolation method; The high-frequency denoising unit is used to filter out high-frequency noise using the db4 wavelet soft thresholding denoising technique, and output a high-fidelity clean sequence.

4. The system according to claim 1, characterized in that, The spatiotemporal analysis module consists of a ground-state data unit, a correction term calculation unit, a spatiotemporal modeling unit, and a deformation trend analysis unit; The ground-state data unit is used to store monitoring data from the initial installation phase as ground-state data. The correction term calculation unit is used to compare subsequent monitoring data with ground state data, calculate the correction term for each monitoring point, and reflect the magnitude and direction of deformation. The spatiotemporal modeling unit is used to construct models using spatiotemporal analysis algorithms to analyze the evolution of deformation in time and space. The deformation trend analysis unit is used to draw deformation trend diagrams, predict future deformation trends, and generate intuitive deformation analysis reports based on correction terms and spatiotemporal models.

5. The system according to claim 1, characterized in that, The derrick and sheave tilt analysis module consists of a tilt calculation unit; the tilt calculation unit is used to determine the tilt angle of the sheave platform and the sheave. For the sheave platform, by analyzing the three-dimensional coordinate data of the monitoring points around it, a local coordinate system is established with the most stable monitoring point as the origin. A plane is fitted, and the tilt angle of the platform is obtained by calculating the angle between the plane normal vector and the horizontal plane. The projection of the normal vector onto the horizontal plane is the tilt direction. For the top wheel, the tilt angle of the top wheel is calculated using the arctangent function based on the ratio of the elevation difference to the distance between the monitoring points on both sides of the top wheel axle, and the tilt direction is determined by combining the three-dimensional coordinate data.

6. A method for real-time monitoring of derrick deformation and sheave tilt based on GNSS technology, wherein the method is implemented by the system described in any one of claims 1-5, characterized in that, The method includes: By deploying one GNSS reference station and eight GNSS monitoring stations, a monitoring and early warning cloud platform is established to form a GNSS monitoring network and collect real-time three-dimensional deformation monitoring data of the derrick. Savitzky-Golay cubic spline interpolation, local outlier factor LOF anomaly detection, and db4 wavelet soft thresholding denoising method were used to clean the three-dimensional deformation monitoring data of the derrick. By combining the ground state correction model, the spatiotemporal deformation characteristics of the derrick are visualized and analyzed to reveal the deformation trend of the derrick; Based on the GNSS monitoring station network configuration, the tilt angles of the derrick and sheave are calculated using the monitoring data after cleaning.

7. The method according to claim 6, characterized in that, The methods for cleaning derrick three-dimensional deformation monitoring data using Savitzky-Golay cubic spline interpolation, local outlier factor LOF anomaly detection, and db4 wavelet soft thresholding denoising include: Missing interpolation and preliminary smoothing: Monitoring data of the derrick , , Three single-dimensional sequences are executed point by point. Savitzky-Golay Filtering: Within a sliding window of width 2m+1=11, where m represents the half-width of the window, a cubic polynomial is used to fit the local data: ； Least squares fit to local data, the coefficient vector is: ； in, For the first in the window i+k The original observations of each epoch, i The index of the current point to be estimated. for Vandermonde matrix, k For relative indexes within the window, p For the order of the polynomial, The coefficients to be determined are: For any missing epoch, the vector of original observations within the window is used. t j ,Will t j Substituting into the cubic polynomial yields the interpolation result. ( t j ); Spatial anomaly detection: Construct a vector from the three-dimensional increments of the same epoch. ,in, They represent the distances in the X, Y, and H directions, respectively. Savitzky-Golay Calculate the deformation increment after processing. k -Locally reachable density in the neighborhood: ； in, The three-dimensional deformation vector of the current center point. It is k - Neighborhood Vector of any neighboring point within, Represents the vector of the nearest point To its first k The Euclidean distance between the nearest neighbor vectors. Then by and The closest k = Consists of 20 points; This leads to the LOF factor: ； when When an outlier is identified, it is removed from the list; the missing location is then re-entered within the same window. Savitzky- Golay Polynomial extrapolation complement; High-frequency noise reduction: The cleaned sequence was decomposed using db4 wavelet J=5 levels, with soft thresholding applied to the detail coefficients. ； in, For the first j Layer k Wavelet detail coefficients, This represents the Euclidean distance, and MAD is the absolute deviation of the median of the detail coefficients. For sequence length, The threshold is used; the reconstructed signal is the following final clean sequence: ； in, The wavelet decomposition level; For the first Layer scaling function basis; For the first j Layer wavelet function basis; These are approximation coefficients.

8. The method according to claim 6, characterized in that, Methods for visually analyzing the spatiotemporal deformation characteristics of the derrick using a ground-state correction model to reveal its deformation trend include: The monitoring data from the initial installation phase is stored as baseline data; By comparing subsequent monitoring data with ground state data, correction terms are calculated for each monitoring point to reflect the magnitude and direction of deformation. A model is constructed using spatiotemporal analysis algorithms to analyze the evolution of deformation in time and space; Based on the correction terms and the spatiotemporal model, a deformation trend diagram is drawn to predict future deformation trends and generate an intuitive deformation analysis report.

9. The method according to claim 6, characterized in that, Based on the GNSS monitoring station network configuration, methods for calculating the tilt angles of the derrick and sheave using post-cleaning monitoring data include: Calculation of derrick tilt angle: ; in, a , b These are the parameters to be determined; Calculation of the tilt angle of the sheave wheel: Assume that there are two GNSS monitoring stations, A and B, with a distance of L between them. Obtain the elevation data of A and B from the monitoring data, which are H respectively. A and H B Calculate the elevation difference ΔH = H between the two monitoring points. A -H B ; Assuming the sheave axle was originally horizontal, when it tilts, the angle of tilt is... θ calculate: θ ≈ΔH / L is based on the assumption of a small angle approximation, that is, when the tilt angle is less than a preset threshold, θ ≈tan θ =ΔH / L; If the tilt angle is greater than the preset threshold, the arctangent function is used for calculation, i.e. θ =arctan(ΔH / L).

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