Plateau area oil tank subsidence observation system and method

Abstract

The application discloses a kind of plateau area oil tank settlement observation systems and methods, applicable to the unmanned high-precision settlement monitoring of plateau permafrost area oil tank.System is along the annular layout of foundation sensing unit of tank wall, divided into multiple detection sets according to ring angle, each detection set is configured set computing terminal, obtains local relative data by the two-way ranging and inclination acquisition of sensing unit, generates deformation characteristics by in-set solution, and global positioning is realized by multiple set cross-validation.Method adopts initial distance matrix calibration, in-set relative deformation variable calculation, multiple set space constraint solution, step-by-step positioning and property discrimination process, and accurate solution is realized by least square method and iterative reference set without external reference, which can effectively distinguish local settlement, overall rigid body displacement and environmental disturbance.The application discards traditional external reference, solves the problem of plateau reference drift, large monitoring error and difficult identification of local settlement.

Description

Technical Field

[0001] This invention belongs to the technical field, specifically relating to a system and method for monitoring the settling of oil tanks in plateau areas. Background Technology

[0002] Cylindrical welded steel oil tanks, as core facilities for strategic energy reserves such as petroleum and aviation kerosene, hold an irreplaceable position in the energy security system of plateau permafrost regions. Foundation treatment in these areas typically employs a structure combining graded crushed stone replacement layer with a ring-shaped reinforced concrete foundation to address the unique challenges of frost heave, thaw settlement, and drastic seasonal temperature variations characteristic of plateau permafrost regions. However, foundation deformation in permafrost regions exhibits significant localized and gradual characteristics. Under repeated freeze-thaw cycles, non-uniform settlement may occur in the tank foundation. If this is not identified and addressed early, it will directly lead to localized stress concentration in the tank wall, weld cracking, and even oil leakage, causing serious safety and environmental accidents.

[0003] In existing technologies, settlement monitoring of oil storage tanks mainly relies on external geodetic benchmarks (such as leveling benchmarks, GPS control points, or total station backsight points) as absolute references. The absolute elevation changes of each measuring point on the tank are obtained through periodic manual measurements or automated total stations and GPS monitoring stations. However, in plateau permafrost regions, external benchmarks themselves drift slowly due to seasonal frost heave and thaw settlement. Furthermore, the strong atmospheric refraction in plateau areas, large errors in long-distance measurements, and long periods of mountain closure result in extremely poor reliability of benchmark data. More importantly, traditional monitoring can only identify the absolute settlement or overall tilt of the tank, and cannot accurately determine the uneven settlement pattern where local areas settle while other areas remain stable. When the local settlement is small, it is easily masked by changes in the overall attitude, making it impossible to achieve early and accurate identification and location of local settlement. Summary of the Invention

[0004] To address the problems existing in the prior art, the present invention aims to provide a system and method for observing the settlement of oil tanks in plateau regions. By using a distributed relative measurement architecture without external benchmarks and a multi-set cross-validation algorithm, the technical challenge of accurately identifying local uneven settlement of oil tanks in plateau permafrost areas is solved.

[0005] The technical solution adopted in this invention is as follows:

[0006] In a first aspect, the present invention provides a tank settling observation system for oil tanks in plateau areas. The system includes a number of basic sensing units uniformly arranged in a ring along the outer wall of the oil tank, a number of detection sets divided along the ring direction, a set computing terminal corresponding to each detection set, and a remote data processing platform that is communicatively connected to each set computing terminal.

[0007] Each detection set consists of several basic sensing units arranged continuously along the circumferential direction of the tank wall. The set computing terminal of each detection set establishes a bidirectional ranging connection with all the basic sensing units in the detection set.

[0008] Each of the basic sensing units integrates a tilt acquisition module, a two-way ranging module, and a short-range communication module. The basic sensing unit is configured to perform two-way real-time ranging with the computing terminal in this detection set and the adjacent basic sensing units in the same detection set, and to acquire tilt data.

[0009] In conjunction with the first aspect, the present invention provides a first embodiment of the first aspect, wherein the set computing terminal is configured to: calculate the relative deformation between each basic sensing unit in the set based on the difference between the real-time ranging value and the initial calibration distance value between each basic sensing unit in the set, generate local deformation features; and interact with the set computing terminals of other detection sets to obtain relative position information between sets.

[0010] The remote data processing platform is configured to perform cross-validation based on the local deformation characteristics of each detection set and the relative position information between multiple sets, and calculate and determine the absolute displacement direction and displacement magnitude of each basic sensing unit in order to determine the deformation region and deformation properties.

[0011] In conjunction with the first embodiment of the first aspect, the present invention provides a second embodiment of the first aspect, wherein the set computing terminal establishes a bidirectional ranging connection with the set computing terminals of at least two other detection sets to obtain the real-time spatial distance between the set computing terminals; the set computing terminal is further configured to participate in multi-set cross-validation calculation based on the relative deformation between basic sensing units within the set and the real-time spatial distance between sets.

[0012] In conjunction with the first embodiment of the first aspect, the present invention provides a third embodiment of the first aspect, in which all basic sensing units and integrated computing terminals are connected to the industrial DC power supply of the tank area via explosion-proof cables and are powered by a unified external power source.

[0013] Secondly, this invention discloses a method for observing the settlement of oil tanks in plateau areas, based on the aforementioned plateau oil tank settlement observation system, comprising the following steps:

[0014] Step S1. First, perform initial calibration. Before the system is put into use, collect and store the initial distance between each basic sensing unit, the initial distance between each basic sensing unit and its corresponding computing terminal, and the initial distance between each computing terminal to establish an initial distance reference matrix.

[0015] Step S2. Then, each basic sensing unit collects real-time distance data with neighboring units and the terminal of this set, and uploads it to the set computing terminal; the set computing terminal calculates the relative deformation between each basic sensing unit in this detection set based on the difference between the real-time distance and the initial distance. At this time, the relative deformation only represents the degree of deformation, and its displacement direction is yet to be determined.

[0016] Step S3. Then, real-time distance data is exchanged between the computing terminals of each set. Based on the spatial constraint relationship between the computing terminals of at least three detection sets, the remote data processing platform establishes a multi-node distance constraint equation set and solves the absolute displacement vector of each detection set relative to the global reference, thereby determining the absolute displacement direction of each computing terminal.

[0017] Step S4. Finally, based on the absolute displacement direction of each set of computing terminals and combined with the relative deformation within each detection set, determine the specific detection set where displacement occurs, the specific basic sensing unit within that detection set where displacement occurs, the range of deformation influence, and the magnitude of displacement, and distinguish whether the deformation is local settlement of the foundation or disturbance of the external environment.

[0018] In conjunction with the second aspect, the present invention provides a first embodiment of the second aspect, wherein the multi-set cross-validation in step S3 specifically includes:

[0019] S301. Based on the real-time ranging values ​​between all sets of computing terminals in the entire ring, the global coordinates of each set are initially calculated using the least squares method, and the deviation of each set from the initial coordinates is calculated.

[0020] S302. Determine at least three non-adjacent detection sets whose deviation is less than the preset stability threshold and whose internal relative deformation is the smallest as the initial reference set;

[0021] S303. Using the initial reference set as a fixed constraint, recalculate the absolute displacement vector of the remaining detection sets;

[0022] S304. If an initial reference set has an internal relative deformation exceeding the threshold in a subsequent monitoring period, it is removed from the reference set, and the process returns to step S302 to iterate and determine a new reference set until the reference set constitutes a stable global coordinate constraint network.

[0023] In conjunction with the second aspect, the present invention provides a second embodiment of the second aspect, wherein the step-by-step determination in step S4 specifically includes:

[0024] First, by calculating the absolute displacement vector of each set of terminals, the detection sets that have overall displacement are selected;

[0025] Secondly, for the detection set with overall displacement, analyze the distribution of relative deformation of each basic sensing unit inside it, and determine the basic sensing unit whose relative deformation exceeds the threshold as the deformation point.

[0026] Finally, the circumferential interval where the continuous deformation points are located is determined as the deformation region, and the absolute displacement direction and displacement magnitude of each point are determined by the vector superposition result of the relative deformation of each deformation point and the overall displacement of the set.

[0027] In conjunction with the second aspect, the present invention provides a third embodiment of the second aspect, which distinguishes and judges the deformation properties, and the specific rules for distinction are as follows:

[0028] If the deformation area is a local circumferential continuous distribution, and the displacement vector is dominated by the vertical component and shows a continuous cumulative change over time, it is determined to be local foundation settlement.

[0029] If the deformation involves the entire detection set and the displacement vector is dominated by the horizontal component, and changes periodically with temperature or wind force, it is determined to be an external environmental disturbance.

[0030] In conjunction with the second aspect, the present invention provides a fourth implementation of the second aspect. In step S2, when the relative deformation of all basic sensing units in the same detection set is of the same magnitude and in the same direction, it is determined that the detection set as a whole has undergone rigid body displacement. At this time, only the overall displacement trend of the set is recorded, and the internal relative deformation is not calculated for the time being. The absolute displacement is determined after cross-verification with adjacent detection sets in step S3.

[0031] In conjunction with the second aspect, the present invention provides a fifth embodiment of the second aspect, wherein in step S3, when more than 50% of the total number of detection sets simultaneously exhibit absolute displacement of the same direction and magnitude, it is determined to be rigid body motion of the oil tank as a whole. At this time, the current state is marked as overall displacement mode, the local settlement determination is paused, and monitoring is resumed after the overall displacement stabilizes.

[0032] The beneficial effects of this invention are as follows:

[0033] (1) The present invention forms a closed-loop monitoring array by arranging basic sensing units along the tank wall in a circumferential direction, thereby eliminating the dependence on external geodetic reference points and avoiding traditional technical problems such as the drift of reference points due to frost heave and thawing in the plateau permafrost region and large errors in long-distance measurement, thus realizing local settlement monitoring without reference points.

[0034] (2) The present invention adopts a two-layer architecture of intra-set relative solution and inter-set cross-validation. By iteratively solving the spatial constraint relationship between multiple detection sets, it can gradually approach and determine the absolute displacement direction and magnitude of each sensing unit under the condition of no absolute reference, accurately identify the slight uneven settlement involving only local areas, and solve the technical problem that the traditional method can only monitor the overall tilt but cannot identify local deformation.

[0035] (3) This invention utilizes the mathematical redundancy of the full-ring multi-node distance constraint network by dividing the detection set and multi-set cross-validation mechanism to effectively distinguish between local foundation settlement, overall tank tilt and overall rigid body motion caused by environmental disturbance, avoid misjudgment and improve the reliability and accuracy of monitoring results in complex plateau environments. Detailed Implementation

[0036] The present invention will be further explained below with reference to specific embodiments.

[0037] Example 1:

[0038] This embodiment addresses the core technical challenges in monitoring oil tank settlement in high-altitude permafrost regions. These challenges include the susceptibility of external geodetic reference points to drift due to frost heave and thaw settlement, significant errors in long-distance measurements, the ability to mask minor localized uneven settlement with overall attitude changes, and the inability to effectively distinguish between foundation settlement and environmental disturbances. The embodiment provides a settlement observation system and method for oil tanks in high-altitude areas, suitable for long-term unmanned settlement monitoring of various cylindrical welded steel oil tanks in permafrost regions. The core technology employs a distributed relative measurement architecture without external reference points. Through a two-layer logic of in-set relative deformation calculation and multi-detection set cross-validation, it achieves accurate identification, location, and property determination of localized uneven settlement. The entire process does not rely on fixed external reference points and is adaptable to complex application scenarios involving extreme temperature variations, low air pressure, and the difficulty of long-term personnel monitoring in high-altitude areas. This embodiment verifies the complete implementation solution through a clear mathematical calculation model and field test scenarios. Those skilled in the art can implement the system without deviation based on the formulas and procedures outlined in this embodiment.

[0039] As a specific implementation of this application, the observation system of this embodiment includes a number of basic sensing units uniformly arranged in a ring along the outer wall of the oil tank, a number of detection sets divided circumferentially along the tank wall, a set computing terminal corresponding to each detection set, and a remote data processing platform that is communicatively connected to all set computing terminals.

[0040] Furthermore, the basic sensing unit is an integrated miniature explosion-proof sensing module. Each basic sensing unit integrates an inclination acquisition module, a two-way ranging module, and a short-range communication module. The inclination acquisition module is used to collect dual-axis inclination data of corresponding points on the tank wall. The two-way ranging module is used to complete two-way real-time ranging with designated nodes and output high-precision distance values. The short-range communication module is used to realize data interaction with the computing terminal of the set and adjacent basic sensing units in the same set.

[0041] For example, the tilt acquisition module can use a MEMS dual-axis tilt sensor with a measurement accuracy of not less than ±0.001°, the bidirectional ranging module can use a UWB high-precision bidirectional ranging module with a ranging accuracy of not less than ±0.1mm, and the short-range communication module can use a LoRa short-range communication module adapted to industrial explosion-proof scenarios. All modules are integrated into a sealed housing that meets the ExiaIICT4Ga explosion-proof rating and can be adapted to extreme working temperature environments from -45℃ to +85℃ at high altitudes.

[0042] Specifically, each detection set consists of several basic sensing units arranged continuously along the circumference of the tank wall. A single detection set covers an angle range of 30° to 90° around the tank. Each detection set contains 3 to 8 consecutive basic sensing units, and the circumferential spacing between adjacent basic sensing units is 3m to 12m.

[0043] For example, for a 100,000 cubic meter floating roof oil tank commonly used in an oil depot, the tank diameter is 80m and the tank wall circumference is about 251m. 24 basic sensing units can be evenly arranged in a ring along the bottom of the outer wall of the tank, corresponding to the position of the annular foundation. The circumferential spacing between adjacent basic sensing units is about 10.4m. Every 4 consecutive basic sensing units along the circumferential direction are divided into a detection set, and the entire tank is divided into 6 detection sets. Each detection set covers a 60° circumferential angle range. The detection sets are distributed in pairs along the diameter of the tank, forming a symmetrical monitoring architecture.

[0044] Furthermore, the computing terminal of each detection set is fixed at the circumferential center of the detection set, and establishes a two-way ranging connection and communication connection with all basic sensing units in the detection set. The straight-line distance between the computing terminal and the farthest basic sensing unit in the set does not exceed 15m, ensuring ranging accuracy and communication stability.

[0045] Specifically, the integrated computing terminal adopts industrial edge computing equipment that meets the same level of explosion-proof requirements. It integrates a two-way ranging module, a medium-power wireless communication module, an edge computing chip, and a wired communication interface, all of the same specifications as the basic sensing unit. The two-way ranging module is used to complete two-way real-time ranging with the integrated computing terminal of the basic sensing unit and other detection sets within the same set. The medium-power wireless communication module is used to realize long-distance data interaction between different detection sets. The edge computing chip is used to complete the calculation of data within the set, the generation of local deformation features, and related calculations for participating in multi-set cross-validation.

[0046] As a specific implementation of this application, all basic sensing units and integrated computing terminals are connected to the explosion-proof certified industrial DC power supply in the tank area through explosion-proof and flame-retardant armored cables. They are powered by a unified external power supply, which can avoid the risks of insufficient battery life and aging failure in extreme high-altitude environments, while meeting the explosion-proof safety requirements of the oil tank area.

[0047] Furthermore, the remote data processing platform can be deployed at the local monitoring center of the oil depot or at the cloud-based monitoring platform. It can establish a stable connection with all aggregate computing terminals through wired or wireless communication networks to receive local deformation characteristics and inter-aggregate ranging data uploaded by each aggregate computing terminal, and complete multi-aggregate cross-validation calculation, deformation area location, deformation property determination, and graded early warning output.

[0048] Understandably, the aforementioned hardware architecture, through a closed-loop sensor array deployed along the tank wall, completely eliminates the reliance on geodetic reference points outside the tank area, fundamentally avoiding the core problems of reference point frost heave and thaw drift and large long-distance measurement errors in plateau permafrost regions. At the same time, through the division of the detection set, it achieves the combination of local monitoring and global verification, providing a hardware foundation for the implementation of subsequent settlement observation methods.

[0049] Based on the above observation system, the plateau region oil tank settlement observation method of this embodiment is implemented in a complete and coherent process. First, the initial calibration step is performed. Before the system is put into use, the installation and fixing of all nodes and the initial data collection are completed to establish the initial distance reference matrix.

[0050] Specifically, under calibration conditions where the tank foundation is stable, the tank is unloaded, and there is no environmental disturbance, three types of initial distance data are collected and stored. The first type is the initial distance between adjacent basic sensing units within the same detection set; the second type is the initial distance between each basic sensing unit and the set computing terminal of its respective detection set; and the third type is the initial distance between the set computing terminals of each detection set. Based on all the initial distance data, an initial distance reference matrix for the entire tank ring is constructed. The matrix construction formula is as follows:

[0051] (1)

[0052] In the formula, D0 is the initial distance reference matrix of the entire ring, D s0 D is the initial distance submatrix for adjacent sensing units within the same set. t0 D is the initial distance submatrix between the sensing unit and the computing terminal of its set. g0 This is the initial distance submatrix between each set of computing terminals; simultaneously, the initial tilt angle data of all basic sensing units are collected and stored in the local storage units of the remote data processing platform and the corresponding set of computing terminals.

[0053] Understandably, the initial distance reference matrix provides a unique static reference for all subsequent deformation calculations, eliminating the need to introduce external reference data throughout the process and ensuring the self-consistency and stability of the monitoring process.

[0054] After initial calibration, the real-time monitoring process begins. Each basic sensing unit collects real-time distance data from adjacent basic sensing units and the computing terminal of its respective set according to a preset monitoring cycle. Simultaneously, it collects its own real-time tilt angle data and ambient temperature data, and uploads them to the computing terminal of its respective set through a short-range communication module.

[0055] For example, the monitoring cycle can be configured according to the service life of the oil tank and the stability of the foundation. The monitoring cycle for newly commissioned oil tanks can be set to 10 minutes / time, and for oil tanks that have been in use for more than 3 years and whose foundations are becoming more stable, the monitoring cycle can be set to 30 minutes / time. Under extreme weather conditions, the monitoring cycle can be increased to 1 minute / time to adapt to the monitoring needs of different scenarios.

[0056] Furthermore, after receiving the raw collected data, the computing terminal first performs temperature drift correction on the measured distance and tilt angle data to eliminate systematic errors caused by the extreme diurnal temperature difference at high altitudes. The correction formula is as follows:

[0057] (2)

[0058] (3)

[0059] In the formula, d corr The effective distance measurement value after temperature correction, d meas The distance is the original distance value measured by the sensor, α is the nominal temperature coefficient of the ranging module, and T is the distance measured by the sensor. meas The ambient temperature is collected in real time, T0 is the ambient temperature at the initial calibration time, and θ is the ambient temperature at the initial calibration time. corr θ is the effective tilt angle value after temperature correction. meas k is the original tilt angle value measured by the sensor. θ This is the nominal temperature drift coefficient of the tilt module.

[0060] After temperature correction, the computing terminal calculates the relative deformation between each basic sensing unit in this detection set based on the difference between the corrected real-time distance and the corresponding initial distance in the initial distance reference matrix. The calculation formula is as follows:

[0061] (4)

[0062] In the formula, Let dcorr(i,j) be the relative deformation between node i and node j, and dcorr(i,j) be the corrected real-time distance measurement between the two nodes. 0(i,j) The initial calibration distance between the two nodes is given. The relative deformation obtained at this time only represents the degree of deformation of the corresponding point, and its displacement direction is in an undetermined state, which needs to be determined through subsequent multi-set cross-validation.

[0063] Specifically, after calculating the relative deformation, the computing terminal simultaneously generates a local deformation feature vector for the detection set based on the distribution of relative deformation of all basic sensing units within the set. The vector construction formula is as follows:

[0064] (5)

[0065] In the formula, V is the local deformation feature vector of a single detection set, and n is the number of basic sensing units in the detection set. This represents the relative deformation of the corresponding sensing unit. This represents the change in tilt angle corresponding to the sensing unit.

[0066] As a specific implementation of this application, the computing terminal performs a preliminary judgment on the deformation distribution within the set during the generation of local deformation feature vectors. When the relative deformation of all basic sensing units within the same detection set is of the same magnitude and in the same direction, it is determined that the detection set as a whole has undergone rigid body displacement. At this time, only the overall displacement trend of the detection set is recorded, and the internal relative deformation is not calculated temporarily. The absolute displacement is determined after cross-verification with adjacent detection sets, thereby reducing the amount of invalid calculation and improving the solution efficiency.

[0067] After completing the calculation of relative deformation within the set and the generation of local deformation features, the computing terminals of each set interact with each other through a medium-power wireless communication module to exchange real-time distance data and local deformation features. Based on the spatial constraint relationship between the computing terminals of at least three detection sets, the remote data processing platform establishes a multi-node distance constraint equation set and calculates the absolute displacement vector of each detection set relative to the global reference, thereby determining the absolute displacement direction of each computing terminal.

[0068] Specifically, the multi-node distance constraint equation system is constructed as follows:

[0069] m=1,2,……M(6)

[0070] In the formula, (x,y,z) represents the real-time global three-dimensional coordinates of the computing terminal of the set to be solved, (x... m ,y m ,z m ) represents the initial global coordinates for calculating the terminal of the m-th reference set. The real-time ranging value between the two computing terminals is the corrected value, M is the number of selected reference sets, and M≥3.

[0071] Furthermore, the optimal solution to the above system of equations is obtained using the least squares method, and the objective function is as follows:

[0072] (7)

[0073] After obtaining the real-time global coordinates of the computing terminal for the dataset to be solved, the difference between these coordinates and the initial calibration coordinates yields the absolute displacement vector of the detection dataset. , where Δx is the radial displacement component, Δy is the circumferential displacement component, and Δz is the vertical settlement component.

[0074] Furthermore, the solution process for the above multi-set cross-validation achieves stable solution by iterating over a benchmark set. The selection and iteration criteria for the benchmark set are as follows:

[0075] (8)

[0076] In the formula, Let m be the absolute displacement vector magnitude of the m-th detection set. The preset stability threshold, Let be the maximum relative deformation within the m-th detection set. This is the preset internal deformation threshold.

[0077] Specifically, the remote data processing platform first calculates the global coordinates of each detection set based on the real-time ranging values ​​between all sets of computing terminals in the entire ring, and calculates the deviation between the real-time coordinates of each detection set and the initial calibration coordinates. Then, at least three non-adjacent detection sets that meet the judgment condition of Equation (8) and have the smallest deviation are determined as the initial reference set. Then, the absolute displacement vectors of the remaining detection sets are recalculated using Equations (6) and (7) with the initial reference set as a fixed constraint. If an initial reference set no longer meets the judgment condition of Equation (8) in subsequent monitoring cycles, it is removed from the reference set, and a new reference set is determined iteratively until the reference set constitutes a stable global coordinate constraint network.

[0078] For example, stability threshold The internal deformation threshold can be set to 0.2mm. It can be set to 0.1mm to ensure that the reference set itself is in a stable and undeformed state, providing reliable constraints for global solution. At the same time, through the iterative update mechanism, it avoids the solution error caused by the deformation of the reference set itself, further improving the accuracy of the monitoring results.

[0079] Optionally, during the calculation of the absolute displacement vector, the tilt angle data collected by each basic sensing unit can be used for auxiliary correction. When the absolute displacement vector calculated by the set computing terminal of a certain detection set is inconsistent with the tilt angle change trend of the basic sensing unit in this set, a secondary calculation can be triggered to eliminate abnormal ranging data and ensure the reliability of the calculation results.

[0080] After completing the calculation of the absolute displacement vector of each detection set, the remote data processing platform, based on the absolute displacement direction of each set's computing terminal and combined with the relative deformation within each detection set, determines step by step the specific detection set where displacement occurs, the specific basic sensing unit within that detection set where displacement occurs, the range of deformation influence, and the magnitude of displacement, and distinguishes between local settlement of the foundation or disturbance of the external environment.

[0081] Specifically, the above-mentioned step-by-step determination process first filters out detection sets with overall displacement by using the absolute displacement vectors of each set's computing terminals; second, for detection sets with overall displacement, it analyzes the relative deformation distribution of each basic sensing unit within them, identifying basic sensing units whose relative deformation exceeds a preset deformation threshold as deformation points; finally, it defines the circumferential interval where continuous deformation points are located as deformation regions, and determines the absolute displacement direction and magnitude of each deformation point by the vector superposition result of the relative deformation of each deformation point and the overall displacement of its corresponding detection set. The superposition formula is as follows:

[0082] (9)

[0083] In the formula, This is the final absolute displacement vector of the deformation point. This represents the overall absolute displacement vector of the detection set to which the deformation point belongs. Let be the relative deformation vector of the deformation point within the set.

[0084] For example, the deformation threshold can be set according to the settlement limit of the oil tank design specification. For an oil tank with a diameter of 80m, the settlement difference limit between adjacent measuring points specified in the design specification of cylindrical steel welded oil tank is 1.8mm. The deformation threshold can be set to 0.5mm to achieve early identification and warning of trace settlement.

[0085] Furthermore, after determining the deformation region and displacement magnitude, the remote data processing platform distinguishes the deformation properties based on the distribution characteristics of the deformation, the direction of the displacement vector, and the trend of time change.

[0086] Specifically, if the deformation area is a local circumferential continuous distribution, and the displacement vector is mainly composed of the vertical component and shows a continuous cumulative change over time, it is determined to be local foundation settlement; if the deformation involves the entire detection set and the displacement vector is mainly composed of the horizontal component and shows a periodic reciprocating change with temperature or wind force, it is determined to be external environmental disturbance.

[0087] Understandably, the above-mentioned rules for distinguishing deformation properties can effectively eliminate interference from tank elastic deformation caused by environmental factors such as extreme temperature differences, strong winds, and earthquake vibrations in plateau areas, avoid misjudgments, and ensure the reliability of settlement monitoring results.

[0088] As a specific implementation of this application, during the multi-set cross-validation process, when more than 50% of the total number of detection sets simultaneously exhibit absolute displacements of the same direction and magnitude, it is determined to be the overall rigid body motion of the oil tank. At this time, the current state is marked as the overall displacement mode, the local settlement determination is paused, and monitoring is resumed after the overall displacement stabilizes. This avoids the interference of non-safety-risk working conditions such as uniform settlement and overall translation of the oil tank on the local settlement determination, and further reduces the false alarm rate.

[0089] In some embodiments, after determining that there is local settlement of the foundation, the remote data processing platform can trigger a graded early warning based on the displacement magnitude and the limits of the oil tank design specifications; at the same time, it can predict the subsequent settlement trend based on the historical settlement sequence using a grey GM(1,1) prediction model. The time response of the model is as follows:

[0090] (10)

[0091] In the formula, This is the time series of the original settlement. This is a sequence generated by cumulative addition, where 'a' is the development coefficient and 'b' is the gray action amount. This is the predicted settlement value for the (k+1)th cycle. This model can quantitatively predict the settlement development trend and anticipate safety risks in advance.

[0092] For example, this embodiment conducts a continuous monitoring test for several months on a 100,000 cubic meter floating roof oil tank at an airport fuel depot in a high-altitude area. The tank has a diameter of 80m and a wall height of 21.8m. It is located in a permafrost region in a high-altitude area with an annual extreme temperature difference of 75℃ and more than 110 days of strong winds per year. The test covers four typical working conditions, and the specific implementation process is as follows.

[0093] As a typical working condition verification scenario in this embodiment, for the scenario of eliminating misjudgments caused by earthquake vibration, multiple aftershocks occurred during the test period, with the epicenter 120km away from the tank area. Before the earthquake, the system was in a normal monitoring state with a monitoring cycle of 30 minutes / time. When the earthquake was triggered, the system automatically increased the monitoring cycle to 1 minute / time.

[0094] During the first monitoring period after the earthquake, the basic sensor units of detection sets A, C, and E all showed a maximum tilt change of 0.005° and a maximum relative deformation of 0.7 mm, triggering a system early warning. The remote data processing platform calculated the absolute displacement vector of each detection set using equation (7) and found that the horizontal component of all deformations accounted for 92%, while the vertical component accounted for only 8%. Moreover, the monitoring data after the earthquake showed that all deformations had fully recovered and there was no continuous accumulation trend, which fully met the judgment rules for external environmental disturbances. Therefore, the system automatically eliminated misjudgments, only recorded earthquake events and corresponding data, and did not trigger formal early warnings, thus avoiding invalid alarms caused by non-settlement factors.

[0095] Furthermore, for the early identification scenario of trace local settlement, during the monitoring period of the third month of the experiment, the system calculated the relative deformation of the 2# and 3# basic sensor units of the detection set A by formula (4) as 0.58mm and 0.62mm respectively. After superimposing the overall displacement of the detection set by formula (9), the absolute settlement of the two points was 0.61mm and 0.65mm respectively, and the settlement difference between adjacent measuring points was 0.4mm, which was lower than the preset first-level warning threshold of 0.8mm.

[0096] The system, through step-by-step positioning logic, determines the deformation area to be the circumferential 0°-30° range of the tank foundation, corresponding to a bearing area of ​​approximately 126m². 2 The subsidence was determined to be a minor localized settlement caused by the initial thawing of the permafrost, posing no safety risk. Only the settlement trend was recorded, and the monitoring cycle for the area was automatically increased to 15 minutes per instance to continuously track the settlement development without triggering any warnings.

[0097] Specifically, for local settlement conditions exceeding the warning threshold, during the monitoring period of the 8th month of the experiment, the system calculated the relative deformation of the 3#, 4# and 5# basic sensor units of the detection set B using formula (4) as 1.22mm, 1.45mm and 1.31mm respectively, and the maximum settlement difference between adjacent measuring points was 1.2mm, which exceeded the preset 1.0mm secondary warning threshold.

[0098] The system calculates the overall displacement of the detection set B using equations (6) and (7) to be only 0.12 mm. The deformation is concentrated in three continuous sensing units within the set, and the deformation area is located in the circumferential range of 60° to 105° around the tank base, corresponding to a tank base bearing area of ​​approximately 210 m². 2 The maximum absolute settlement was 1.42 mm. Subsequently, based on the continuous settlement sequence of the area over the past 3 months, the system completed the trend fitting through the GM(1,1) model of Equation (10) and obtained the development coefficient a=-0.032. It was predicted that at the current settlement rate, the maximum settlement in the area would reach 1.85 mm in 3 months, exceeding the national standard limit of 1.8 mm. Therefore, the system automatically triggered an orange level 2 warning and simultaneously pushed the settlement location, settlement amount, and development trend prediction results to the oil depot safety management department, providing accurate data support for subsequent foundation treatment.

[0099] Optionally, for the case of uniform settlement of the tank as a whole, during the monitoring period of the 10th month of the test, the system calculates the absolute displacement vector of the set calculation terminal of the six detection sets of the whole tank through Equation (7). All of them are in the vertical downward direction, with a magnitude between 0.88mm and 0.92mm, in the same direction and of the same magnitude, and the maximum difference is less than 0.04mm. At the same time, the relative deformation in each detection set is less than 0.1mm, with no local deformation characteristics. More than 50% of the detection sets show displacement in the same direction and of the same magnitude, which meets the judgment conditions of the overall rigid body motion. The system automatically judges that the tank is uniformly settled as a whole, with no local non-uniform deformation and no safety risk. It marks the current state as the overall displacement mode, does not trigger any warning, only records the overall settlement amount, and continuously tracks subsequent changes.

[0100] In some embodiments, all monitoring data, calculation results, and early warning information can be synchronously stored in the local storage unit of the remote data processing platform to generate historical trend curves and monitoring reports, providing data support for the stability assessment of oil tank foundations and the formulation of maintenance and repair plans.

[0101] In summary, this embodiment, through a distributed monitoring architecture without external benchmarks, completely avoids the industry pain points of external benchmark drift and large long-distance measurement errors in plateau permafrost regions. It achieves complete logic of intra-set relative calculation and multi-set cross-validation through a clear mathematical solution model, accurately identifying localized minor uneven settlement of oil tanks, effectively distinguishing between foundation settlement, overall rigid body motion of the tank, and environmental disturbance deformation. Field verification under various typical working conditions proves that the solution is suitable for long-term monitoring needs in unattended, extreme environments in plateau regions, significantly improving the reliability, accuracy, and safety of plateau oil tank settlement monitoring, and providing strong technical support for the safe and stable operation of plateau energy storage facilities.

[0102] This invention is not limited to the optional embodiments described above, and anyone can derive other various forms of products based on the inspiration of this invention. The specific embodiments described above should not be construed as limiting the scope of protection of this invention; the scope of protection of this invention should be determined by the claims, and the specification can be used to interpret the claims.

Claims

1. A sedimentation monitoring system for oil tanks in plateau areas, specifically for oil tanks, characterized in that: It includes several basic sensing units evenly arranged in a ring along the outer wall of the oil tank, several detection sets divided along the ring direction, a set computing terminal set corresponding to each detection set, and a remote data processing platform that is communicatively connected to each set computing terminal. Each detection set consists of several basic sensing units arranged continuously along the circumferential direction of the tank wall. The set computing terminal of each detection set establishes a bidirectional ranging connection with all the basic sensing units in the detection set. Each of the basic sensing units integrates a tilt acquisition module, a two-way ranging module, and a short-range communication module. The basic sensing unit is configured to perform two-way real-time ranging with the computing terminal in this detection set and the adjacent basic sensing units in the same detection set, and to acquire tilt data.

2. The plateau-area oil tank settling observation system according to claim 1, characterized in that, The set computing terminal is configured to: calculate the relative deformation between each basic sensing unit in the set based on the difference between the real-time ranging value and the initial calibration distance value between each basic sensing unit in the set, and generate local deformation features; It also interacts with the data computing terminals of other detection sets to obtain relative position information between sets; The remote data processing platform is configured to perform cross-validation based on the local deformation characteristics of each detection set and the relative position information between multiple sets, and calculate and determine the absolute displacement direction and displacement magnitude of each basic sensing unit in order to determine the deformation region and deformation properties.

3. The plateau-area oil tank settling observation system according to claim 2, characterized in that, The set computing terminal establishes a bidirectional ranging connection with the set computing terminals of at least two other detection sets to obtain the real-time spatial distance between the set computing terminals; the set computing terminal is also configured to participate in multi-set cross-validation calculation based on the relative deformation between basic sensing units within the set and the real-time spatial distance between sets.

4. The plateau-area oil tank settling observation system according to claim 2, characterized in that, All basic sensing units and integrated computing terminals are connected to the industrial DC power supply in the tank area via explosion-proof cables, and are powered by a unified external power source.

5. A method for observing the settlement of oil tanks in plateau areas, implemented based on the plateau oil tank settlement observation system described in any one of claims 2-4, characterized in that, Includes the following steps: Step S1. First, perform initial calibration. Before the system is put into use, collect and store the initial distance between each basic sensing unit, the initial distance between each basic sensing unit and its corresponding computing terminal, and the initial distance between each computing terminal to establish an initial distance reference matrix. Step S2. Then, each basic sensing unit collects real-time distance data with neighboring units and the terminal of this set, and uploads it to the set computing terminal; the set computing terminal calculates the relative deformation between each basic sensing unit in this detection set based on the difference between the real-time distance and the initial distance. At this time, the relative deformation only represents the degree of deformation, and its displacement direction is yet to be determined. Step S3. Then, real-time distance data is exchanged between the computing terminals of each set. Based on the spatial constraint relationship between the computing terminals of at least three detection sets, the remote data processing platform establishes a multi-node distance constraint equation set and solves the absolute displacement vector of each detection set relative to the global reference, thereby determining the absolute displacement direction of each computing terminal. Step S4. Finally, based on the absolute displacement direction of each set of computing terminals and combined with the relative deformation within each detection set, determine the specific detection set where displacement occurs, the specific basic sensing unit within that detection set where displacement occurs, the range of deformation influence, and the magnitude of displacement, and distinguish whether the deformation is local settlement of the foundation or disturbance of the external environment.

6. The method for observing the settlement of oil tanks in plateau areas according to claim 5, characterized in that, The multi-set cross-validation in step S3 specifically includes: S301. Based on the real-time ranging values ​​between all sets of computing terminals in the entire ring, the global coordinates of each set are initially calculated using the least squares method, and the deviation of each set from the initial coordinates is calculated. S302. Determine at least three non-adjacent detection sets whose deviation is less than the preset stability threshold and whose internal relative deformation is the smallest as the initial reference set; S303. Using the initial reference set as a fixed constraint, recalculate the absolute displacement vector of the remaining detection sets; S304. If an initial reference set has an internal relative deformation exceeding the threshold in a subsequent monitoring period, it is removed from the reference set, and the process returns to step S302 to iterate and determine a new reference set until the reference set constitutes a stable global coordinate constraint network.

7. The method for observing the settlement of oil tanks in plateau areas according to claim 5, characterized in that, The step-by-step determination in step S4 specifically includes: First, by calculating the absolute displacement vector of each set of terminals, the detection sets that have overall displacement are selected; Secondly, for the detection set with overall displacement, analyze the distribution of relative deformation of each basic sensing unit inside it, and determine the basic sensing unit whose relative deformation exceeds the threshold as the deformation point. Finally, the circumferential interval where the continuous deformation points are located is determined as the deformation region, and the absolute displacement direction and displacement magnitude of each point are determined by the vector superposition result of the relative deformation of each deformation point and the overall displacement of the set.

8. The method for observing the settlement of oil tanks in plateau areas according to claim 5, characterized in that, The specific rules for distinguishing and judging deformation properties are as follows: If the deformation area is a local circumferential continuous distribution, and the displacement vector is dominated by the vertical component and shows a continuous cumulative change over time, it is determined to be local foundation settlement. If the deformation involves the entire detection set and the displacement vector is dominated by the horizontal component, and changes periodically with temperature or wind force, it is determined to be an external environmental disturbance.

9. The method for observing the settlement of oil tanks in plateau areas according to claim 5, characterized in that, In step S2, when the relative deformation of all basic sensing units in the same detection set is of the same magnitude and in the same direction, it is determined that the detection set as a whole has undergone rigid body displacement. At this time, only the overall displacement trend of the set is recorded, and the internal relative deformation is not calculated. The absolute displacement is determined after cross-verification with adjacent detection sets in step S3.

10. A method for observing the settlement of oil tanks in plateau areas according to claim 5, characterized in that, In step S3, when more than 50% of the total number of detection sets simultaneously show absolute displacement of the same direction and magnitude, it is determined that the oil tank is in overall rigid body motion. At this time, the current state is marked as overall displacement mode, the local settlement determination is paused, and monitoring is resumed after the overall displacement stabilizes.