Substation foundation settlement prediction analysis system and method based on industrial cloud platform

Abstract

The present application relates to the technical field of online monitoring, and is a substation foundation settlement prediction analysis system and method based on an industrial cloud platform, which specifically comprises the following steps: establishing a digital grid unit of a three-dimensional space of a substation, collecting real-time working condition data and underground water level data of all equipment in the substation, and predicting real-time settlement rate and cumulative settlement of each grid unit; outputting real-time sensitivity index of the equipment through a sensitivity index model; constructing a double risk propagation network, calculating a settlement risk probability value and a global risk entropy value, and generating a three-dimensional visual maintenance navigation. The present application solves the problem of low prediction accuracy of substation settlement risk caused by insufficient integration of multi-source dynamic data and the inability of a static load model to quantify time-varying coupling effect in the prior art.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of online monitoring, and is a substation foundation settlement prediction analysis system and method based on an industrial cloud platform. BACKGROUND

[0002] In the field of power system infrastructure safety, substation foundation settlement prediction is a key technology to ensure stable operation of equipment. However, the existing methods have the following technical problems: the existing settlement analysis is mostly based on a single geological parameter or a static load model, and does not effectively integrate multi-source heterogeneous dynamic data such as equipment vibration, thermal expansion, and gas pressure, resulting in insufficient quantification of time-varying load coupling effects in key areas such as the main transformer area and the GIS area, and difficulty in accurately capturing instantaneous additional stress caused by high-frequency vibration and temperature fluctuations; at the same time, the existing settlement prediction model generally uses homogenization grid division, lacks correlation with the three-dimensional space of equipment geographical coordinates and functional zoning, cannot realize differentiated regional settlement sensitivity grading, and ignores the cascading propagation effect of the dual coupling of electrical connection and physical proximity between equipment, resulting in risk positioning deviation; in addition, the existing settlement risk prediction mostly relies on fixed threshold to judge equipment failure risk, and does not establish a dynamic tolerance adjustment mechanism based on real-time working conditions (such as main transformer load current, GIS bus angle, and cable terminal stress), making it difficult to adapt to threshold drift problems in complex operating environments. SUMMARY

[0003] The technical problem to be solved by the present application is the low precision of substation settlement risk prediction caused by insufficient integration of multi-source dynamic data and the inability of static load models to quantify time-varying coupling effects in the prior art. The present application proposes a substation foundation settlement prediction analysis system and method based on an industrial cloud platform.

[0004] To achieve the above purpose, the technical scheme of the substation foundation settlement prediction analysis method based on the industrial cloud platform of the present application includes the following steps:

[0005] S1: establishing a digital grid unit of the three-dimensional space of the substation, and correlating the digital grid unit and geographical coordinates with foundation engineering parameters;

[0006] S2: collecting real-time working condition data and underground water level data of all equipment in the substation, and predicting real-time settlement rate and cumulative settlement of each grid unit;

[0007] S3: dynamically adjusting the equipment inclination threshold and settlement failure threshold in the sensitivity index model according to the real-time working condition data, and outputting the real-time sensitivity index of the equipment through the sensitivity index model;

[0008] S4: constructing a dual risk propagation network, calculating the settlement risk probability value and global risk entropy value based on the real-time sensitivity index of the equipment, and generating a three-dimensional visual maintenance navigation.

[0009] Specifically, S1 comprises:

[0010] S11: establishing a three-dimensional coordinate system with the geographic center of the substation as the origin, dividing the substation into a plurality of grid units according to a preset grid unit resolution, obtaining a device list of the substation, and assigning each device with a grid unit code of the grid unit to which the device belongs;

[0011] It should be noted that the grid unit code of each grid unit is stored in the information in the grid unit code ;

[0012] It should be noted that, is the grid unit center point coordinate, wherein i and j are the plane grid unit indexes, and k is the vertical layer index;

[0013] is the foundation stiffness of the foundation where the grid unit is located;

[0014] is the area function code of the device in the grid unit;

[0015] S12: collecting the operation data of the device, binding the real-time operation data of the device with the grid unit, and building a basic operation data model of the substation.

[0016] Specifically, S2 comprises:

[0017] S21: extracting the area function code and real-time operation data of the device in the grid unit;

[0018] S22: establishing a device dynamic load quantification model, inputting the real-time operation data into the device dynamic load quantification model according to the area function code, and outputting dynamic load data of each grid unit, wherein the dynamic load data comprises a main transformer area dynamic load and a GIS area dynamic load;

[0019] It should be noted that the acquisition strategy of the main transformer area dynamic load is specifically:

[0020] A221: measuring the weight of the main transformer body, the weight of the bushing and the weight of the accessories, and calculating the unit area static load , the calculation strategy of which is the static weight of the device in the grid unit divided by the ground contact area of the device;

[0021] A222: installing an acceleration rate sensor on the main transformer base, collecting vibration signals, extracting vibration amplitude and frequency through Fourier transform, and converting them into additional load of the main transformer;

[0022] A223: simultaneously monitoring the oil temperature of the main transformer, calculating the additional load correction term of the foundation caused by thermal expansion and contraction based on the thermal expansion coefficient;​

[0023] A224: According to A221-A223, the dynamic load of the main variable area is calculated , specifically:

[0024] ;

[0025] Wherein, is the static weight of the equipment in the grid unit; is the peak value of the vibration load;

[0026] is the vibration frequency; is the thermal expansion coefficient; is the real-time temperature of the equipment in the grid unit; is the baseline temperature of the equipment in the grid unit;

[0027] It should be noted that the acquisition strategy of the dynamic load of the GIS area is specifically:

[0028] B221: Real-time acquisition through GIS gas chamber pressure sensor ;

[0029] B222: Calculate the additional settlement load caused by pressure change through sealing flange deformation coefficient , specifically:

[0030] ;

[0031] Wherein, is the sealing flange deformation coefficient; is the real-time gas pressure, is the baseline pressure of the gas; is the area of the sealing flange;

[0032] S23: Real-time monitoring of underground water level data in each grid unit, and determining the baseline settlement rate of each grid unit according to the underground water level data;

[0033] Preferably, the calculation strategy of the baseline settlement rate is:

[0034] ;

[0035] Wherein, is the soil creep coefficient;

[0036] is the underground water level influence coefficient; is the static load of the area; is the equipment foundation area; E is the elastic modulus of the soil;

[0037] S24: Extracting dynamic load data and calculating the comprehensive additional stress between equipment in the grid unit.

[0038] Preferably, the comprehensive additional stress between equipment clusters in the grid unit The calculation strategy is specifically:

[0039] ;

[0040] Wherein, is the dynamic load determined according to the area function code of the equipment in the grid unit, is the ground contact area of the equipment in the grid unit;

[0041] Specifically, S2 further comprises the following steps:

[0042] S25: According to S23-S24, the corrected real-time settlement rate is calculated;

[0043] Preferably, the real-time settlement rate The acquisition strategy is specifically:

[0044] ;

[0045] Wherein, is the soil compression index; is the initial void ratio, is the pre-consolidation pressure of the substation soil;

[0046] S26: According to the corrected real-time settlement rate of the grid unit, the cumulative settlement of each grid unit is calculated.

[0047] Preferably, the calculation strategy of the cumulative settlement is:

[0048] ;

[0049] Wherein, is the measured settlement value at the initial time; is the starting time of the basic settlement prediction.

[0050] Specifically, S3 comprises the following specific steps:

[0051] S31: According to the real-time running state of the equipment in each grid unit, the tilt tolerance threshold and the settlement failure threshold changing with the working condition of the equipment in the grid unit are established;

[0052] S32: A settlement sensitivity index model is established, and the equipment sensitivity weight of each grid unit is determined by an analytic hierarchy process algorithm, wherein the sensitivity index model is specifically:

[0053] ;

[0054] wherein, is the device settlement sensitivity of each grid cell; is the device sensitivity weight;

[0055] is the device tilt obtained by the sensor network;

[0056] is the average difference settlement amount between the predicted cumulative settlement amount of the grid cell and the predicted cumulative settlement amount of the neighboring grid;

[0057] is the standard tilt tolerance threshold; is the standard settlement failure threshold;

[0058] S33: Extracting the tilt tolerance threshold and the settlement failure threshold of the device in S31 to dynamically replace and adjust the standard tilt tolerance threshold and the standard settlement failure threshold in the sensitivity index model;

[0059] It should be noted that the dynamic adjustment process includes:

[0060] When the grid cell belongs to the main transformer area, that is, the sensitivity index model is adjusted by the main transformer tilt tolerance threshold, and the main transformer tilt tolerance threshold The acquisition strategy includes:

[0061] ;

[0062] wherein, is the basic tilt tolerance under the rated load of the main transformer;

[0063] is the mechanical slack coefficient of the winding;

[0064] is the real-time load current, is the rated current;

[0065] When the grid cell belongs to the GIS area, that is, the sensitivity index model is adjusted by the GIS tilt tolerance threshold, and the GIS tilt tolerance threshold The acquisition strategy includes:

[0066] ;

[0067] wherein, is the maximum allowable expansion amount of the bellows connected to the device busbar of the GIS area;

[0068] L is the average value of the center distance of the adjacent air chambers of the GIS area equipment;

[0069] It should be noted that the dynamic adjustment process further includes:

[0070] When the grid unit belongs to the main transformer area, that is, the sensitivity index model is adjusted by the main transformer settlement failure threshold, and the acquisition strategy of the main transformer settlement failure threshold includes:

[0071] ;

[0072] Wherein, d is the maximum horizontal displacement allowed by the connecting piece of the main transformer area equipment;

[0073] D is the base diameter of the main transformer area equipment; is the maximum inclination angle allowed by the base of the main transformer area equipment;

[0074] When the grid unit belongs to the GIS area, that is, the sensitivity index model is adjusted by the GIS settlement failure threshold, and the acquisition strategy of the GIS settlement failure threshold includes:

[0075] ;

[0076] Wherein, is the compression allowance of the sealing ring of the GIS area equipment;

[0077] is the length of a single section of the bus; is the allowable angle of bus butt joint;

[0078] S34: Adjust the sensitivity index model by dynamically replacing the adjusted sensitivity index model, and output the real-time sensitivity index of each grid unit.

[0079] Specifically, in S33, the dynamic adjustment process includes:

[0080] When the grid unit belongs to the main transformer area, that is, the sensitivity index model is dynamically adjusted by the main transformer inclination tolerance threshold and the main transformer settlement failure threshold;

[0081] When the grid unit belongs to the GIS area, that is, the sensitivity index model is dynamically adjusted by the GIS inclination tolerance threshold and the GIS settlement failure threshold;

[0082] When the grid unit belongs to the cable trench, that is, the dynamic adjustment of the sensitivity index model includes:

[0083] Collect the operation data of the cable terminal head in the grid unit, and the parameters of the cable terminal head include: the difference between the foundation settlement amounts at both ends of the terminal head and the real-time temperature difference at both ends of the terminal head;

[0084] Import the collected operation data of the cable terminal head into a coupling stress calculation strategy, and calculate the real-time coupling stress of the equipment in the cable trench;

[0085] It should be noted that the coupling stress of the equipment in the cable trench is caused by thermal expansion and settlement;

[0086] Compare the real-time coupling stress of the equipment in the cable trench with the maximum allowable stress of the equipment in the cable trench, when the real-time coupling stress is greater than the maximum allowable stress, take the difference between the foundation settlement amounts at both ends of the terminal head at this time as the cable settlement failure threshold; when the real-time coupling stress is less than or equal to the maximum allowable stress, take the maximum settlement difference allowed in the design of the cable in the factory state as the cable settlement failure threshold;

[0087] According to the cable settlement failure threshold, the sensitivity index model is dynamically adjusted.

[0088] Specifically, S4 includes:

[0089] S41: Obtain the device line transmission capacity and the system total capacity of each grid unit in the substation, and calculate the electrical weight of each grid unit, wherein the calculation strategy of the electrical weight is the ratio of the device line transmission capacity to the system total capacity;

[0090] It should be noted that the greater the proportion of the device line transmission capacity of the grid unit, the more significant the influence of the device failure on the substation, and the higher the risk propagation weight;

[0091] S42: Obtain the physical distance between devices in each grid unit, quantify the risk propagation weight of adjacent devices through a decay function, and obtain a structure weight;

[0092] S43: Construct a dual risk propagation network based on the electrical weight and the structure weight of the substation, wherein the dual risk propagation network is a risk propagation weight matrix of , wherein N is the total number of grid units in the substation, and the comprehensive weight in the risk propagation weight matrix is the sum of the electrical weight and the structure weight.

[0093] Specifically, S4 further includes:

[0094] S44: According to the real-time sensitivity index of the device and the risk propagation weight matrix, calculate the settlement risk probability value of each grid unit;

[0095] Preferably, the calculation strategy of the settlement risk probability value of each grid unit is: ​

[0096] ;

[0097] wherein, is the real-time sensitivity index of the equipment in the i-th grid unit;

[0098] is the comprehensive weight of the risk propagated by the equipment in the i-th grid unit to other grid units;

[0099] S45: synchronously calculate the global risk entropy value of the substation according to the settlement risk probability value;

[0100] Preferably, the calculation strategy of the global risk entropy value is specifically:

[0101] ;

[0102] S46: arrange the settlement risk probability value in descending order from high to low to generate a device settlement risk priority list of the substation, and synchronously generate a three-dimensional visual maintenance navigation of the substation according to the device settlement risk priority list, and take the global risk entropy value as an evaluation index of the overall risk of the substation, and when the global risk entropy value exceeds a preset risk entropy value, an alarm processing is performed and a global emergency plan of the substation is triggered;

[0103] When the global risk entropy value does not exceed the preset risk entropy value, the prediction of the basic settlement of the substation continues.

[0104] In addition, the substation basic settlement prediction analysis system based on the industrial cloud platform comprises the following modules:

[0105] a three-dimensional modeling module, a settlement quantification module, a sensitivity evaluation module, a risk evaluation module and a maintenance navigation module;

[0106] The three-dimensional modeling module is used to establish a digital grid unit of the three-dimensional space of the substation, and associate the digital grid unit and the geographic coordinates with the basic engineering parameters;

[0107] The settlement quantification module is used to collect real-time working condition data and underground water level data of all equipment in the substation, and predict real-time settlement rate and cumulative settlement amount of each grid unit;

[0108] The sensitivity evaluation module dynamically adjusts the equipment inclination threshold and settlement failure threshold in the sensitivity index model according to the real-time working condition data, and outputs the real-time sensitivity index of the equipment through the sensitivity index model;

[0109] The risk evaluation module is used to construct a double risk propagation network, calculate the settlement risk probability value and the global risk entropy value based on the real-time sensitivity index of the equipment;

[0110] The maintenance navigation module generates a three-dimensional visual maintenance navigation according to the evaluation result of the risk evaluation module.

[0111] Compared with the prior art, the technical effects of the present application are as follows:

[0112] The technical scheme realizes fine prediction and differential risk assessment of substation foundation settlement through three-dimensional digital grid modeling and multi-source dynamic load coupling analysis, accurately quantifies the time-varying additional stress of different regions based on three-dimensional grid division of equipment function partition (main transformer area, GIS area, cable trench, etc.) and dynamic load model (vibration-thermal expansion coupling load in main transformer area, gas pressure deformation load in GIS area, static background load in cable trench), solves the problem that the traditional homogenization model cannot reflect the difference between equipment operation characteristics and soil response, and makes the differential characteristics such as instantaneous settlement fluctuation caused by high-frequency vibration in the main transformer area, sensitive settlement of sealed micro-deformation in the GIS area, and long-term creep settlement in the cable trench be separated modeling, which significantly improves the prediction accuracy of settlement speed; secondly, the present application also adjusts the tilt and settlement failure threshold in real time according to the importance of different regional equipment (such as main transformer electromagnetic stability, GIS sealing reliability, and cable terminal head mechanical strength) through a dynamic sensitivity index model, dynamically corrects the tolerance standard in combination with multi-dimensional working condition parameters such as equipment load current, bus angle, and terminal head stress, solves the problem that the fixed threshold cannot adapt to complex operating environment, and makes the risk assessment more in line with the actual equipment tolerance limit; at the same time, the present application also constructs a dual risk propagation network coupled with electrical weight (transmission capacity ratio) and structural weight (distance attenuation function), quantifies the cascading failure probability between equipment, dynamically evaluates the global risk distribution situation in combination with risk entropy, breaks through the limitations of traditional isolated risk assessment, can not only locate high-risk hub equipment (such as high-sensitivity main transformer and adjacent GIS equipment cluster), but also can warn systematic risk accumulation through entropy value change, and generates the final three-dimensional visual maintenance navigation. BRIEF DESCRIPTION OF DRAWINGS

[0113] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor. Among them:

[0114] Figure 1 The flowchart of the substation foundation settlement prediction and analysis method based on the industrial cloud platform of the present application;

[0115] Figure 2 The structure diagram of the substation foundation settlement prediction and analysis system based on the industrial cloud platform of the present application;

[0116] Figure 3 This is a schematic diagram of a process for obtaining cumulative settlement according to the present invention;

[0117] Figure 4 This is a schematic diagram illustrating the process of obtaining the real-time sensitivity index of a device according to the present invention. Detailed Implementation

[0118] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0119] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0120] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0121] Example 1: As Figure 1 As shown in the embodiment of the present invention, the substation foundation settlement prediction and analysis method based on an industrial cloud platform is as follows: Figure 1 As shown, the specific steps include the following:

[0122] S1: Establish digital grid cells in the three-dimensional space of the substation and associate the digital grid cells and geographic coordinates with basic engineering parameters;

[0123] S11: Establish a three-dimensional coordinate system with the geographical center of the substation as the origin, divide the substation into several grid units according to the preset grid unit resolution, obtain the equipment list of the substation, and assign a grid unit code to each equipment.

[0124] For example, in this embodiment, a Cartesian coordinate system is used, with the geographical center of the substation as the origin. The X-axis is parallel to the access road (positive in the east), the Y-axis is perpendicular to the road (positive in the north), and the Z-axis is the elevation (0 for ground level, negative downwards). The resolution of the planar grid unit is determined according to the equipment size and the accuracy requirements of the foundation analysis, with a resolution of 1m × 1m. The vertical direction is divided according to the soil layer distribution (e.g., 0.5m per layer).

[0125] It should be noted that each grid cell has a grid cell code. The information stored in is ;

[0126] It should be noted that, is the grid unit center point coordinates, wherein i and j are the plane grid unit indexes, and k is the vertical layer index;

[0127] is the foundation stiffness of the foundation where the grid unit is located;

[0128] Exemplarily, in the embodiment, The acquisition method of is specifically: obtaining the elastic modulus and Poisson's ratio of each layer of soil through a geological survey report, and calculating the equivalent stiffness of the grid by using the layer summation method;

[0129] is the area function code of the equipment in the grid unit;

[0130] Exemplarily, in the embodiment, when the area function of the equipment in the grid unit belongs to the main transformer room, , wherein the main transformer room includes a main transformer, a cooling system and a firewall;

[0131] When the area function of the equipment in the grid unit belongs to the GIS room or the outdoor GIS equipment area, , wherein the GIS room or the outdoor GIS equipment area includes SF6 gas insulated equipment;

[0132] When the area function of the equipment in the grid unit belongs to the cable trench, , wherein the cable trench includes a cable support and a terminal head;

[0133] When the area function of the equipment in the grid unit belongs to other areas different from the above cases, .

[0134] S12: Collect the operation data of the equipment, bind the real-time operation data of the equipment with the grid unit, and build a basic operation data model of the substation.

[0135] S2: Collect real-time working condition data and underground water level data of all equipment in the substation, as shown in Figure 3 , to predict the real-time settlement rate and cumulative settlement of each grid unit;

[0136] S21: Extract the area function code of the equipment in the grid unit and the real-time operation data;

[0137] S22: Establish a dynamic load quantification model of the equipment, and input the real-time operation data into the dynamic load quantification model according to the area function code, to output dynamic load data of each grid unit, wherein the dynamic load data includes main transformer area dynamic load and GIS area dynamic load;

[0138] It should be noted that the acquisition strategy of the dynamic load of the main transformer area is specifically:

[0139] A221: Measure the weight of the main transformer body (including oil weight, cooling system), bushing and accessories, and calculate the static load per unit area The calculation strategy is the static weight of the equipment in the grid unit divided by the equipment ground area.

[0140] A222: Install an acceleration sensor on the main transformer base to collect vibration signals (100-600Hz as the main frequency), extract the vibration amplitude and frequency through Fourier transform, and convert it into the additional load of the main transformer;

[0141] A223: Monitor the oil temperature of the main transformer at the same time, calculate the additional load correction term of thermal expansion and contraction on the foundation based on the thermal expansion coefficient;

[0142] A224: Calculate the dynamic load of the main transformer area according to A221-A223 , Specifically:

[0143] ;

[0144] Among them, The static weight of the equipment in the grid unit; The peak value of the vibration load;

[0145] The vibration frequency; The thermal expansion coefficient; The real-time temperature of the equipment in the grid unit; The baseline temperature of the equipment in the grid unit;

[0146] Exemplarily, in the present embodiment, it should be noted that,

[0147] It is a periodic vibration load (sinusoidal change with time), The peak value of the vibration load is calibrated through equipment operating test; The thermal expansion effect caused by temperature (modified by exponential decay);

[0148] It should be noted that the acquisition strategy of the dynamic load of the GIS area is specifically:

[0149] B221: Real-time acquisition of ;

[0150] Exemplarily, in the present embodiment, the gas baseline pressure Take the rated working pressure of the equipment 0.6MPa;

[0151] B222: Additional settlement load caused by pressure change through sealing flange deformation coefficient calculation , specifically:

[0152] ;

[0153] wherein, is the sealing flange deformation coefficient; is the real-time gas pressure, is the gas baseline pressure; is the sealing flange area;

[0154] Exemplarily, in the present embodiment, it is necessary to note that the GIS area dynamic load reflects the dynamic load of the sealing flange micro-deformation on the foundation;

[0155] S23: Real-time monitoring of underground water level data in each grid unit, and determining the baseline settlement rate of each grid unit according to the underground water level data;

[0156] Preferably, the baseline settlement rate is calculated by the following strategy:

[0157] ;

[0158] wherein, is the soil creep coefficient;

[0159] Exemplarily, in the present embodiment, the soil creep coefficient is obtained through indoor compression test;

[0160] is the underground water level influence coefficient; is the static load of the area; is the equipment foundation area; E is the soil elastic modulus;

[0161] S24: Extracting dynamic load data and calculating the comprehensive additional stress between equipment in the grid unit.

[0162] Preferably, the comprehensive additional stress between equipment clusters in the grid unit is calculated by the following strategy:

[0163] ;

[0164] wherein, is the dynamic load determined according to the area function code of the equipment in the grid unit, is the ground contact area of the equipment in the grid unit;

[0165] S25: According to S23-S24, the corrected real-time settlement rate is calculated and obtained;

[0166] Preferably, the real-time settlement rate The acquisition strategy is specifically:

[0167] ;

[0168] Wherein, is the compression index of the soil body; is the initial void ratio, is the pre-consolidation pressure of the substation soil body;

[0169] S26: According to the real-time settlement rate of the grid unit after correction, the cumulative settlement of each grid unit is calculated.

[0170] Preferably, the calculation strategy of the cumulative settlement is:

[0171] ;

[0172] Wherein, is the measured settlement value at the initial time; is the starting time of the basic settlement prediction.

[0173] Exemplarily, in the embodiment, it needs to be pointed out that the load type of the cable trench is significantly different from the main transformer and GIS equipment:

[0174] For the main transformer area: the device self-weight (static), vibration load (dynamic) and thermal expansion (temperature related) are mainly considered, and the load has dynamic time-varying characteristics.

[0175] GIS area: the additional stress caused by the change of SF6 gas pressure is mainly considered, which involves the sensitivity of the sealing structure to micro-deformation, and the pressure-deformation relationship needs to be quantified separately.

[0176] Cable trench: usually with static load (cable weight, trench self-weight) and stable environmental load (such as underground water level, soil self-weight), dynamic change is small, and there is no high-frequency vibration or gas pressure and other strong time-varying factors.

[0177] Therefore, in the device dynamic load quantification model established in the embodiment, the grid unit of the device whose area function belongs to the cable trench, that is, the grid unit of is simplified as a static background load.

[0178] S3: According to the real-time working condition data, dynamically adjust the device inclination threshold and settlement failure threshold in the sensitivity index model, and output the real-time sensitivity index of the device through the sensitivity index model, as shown in Figure 4 ;

[0179] S31: According to the real-time running state of the device in each grid unit, the inclination tolerance threshold and the settlement failure threshold are established with the change of the working condition of the device in the grid unit;

[0180] S32: Establish a settlement sensitivity index model, and determine the device sensitivity weight of each grid unit through an analytic hierarchy process algorithm according to the influence degree of the device on the power grid safety, wherein the sensitivity index model is specifically:

[0181] ;

[0182] wherein, is the device settlement sensitivity of each grid unit; is the device sensitivity weight;

[0183] Exemplarily, in the embodiment, for the device in the main transformer area, ;

[0184] for the device in the GIS area, ; for the device in the cable trench, ;

[0185] is the device inclination obtained by the sensor network;

[0186] is the average value of the difference settlement amount between the predicted cumulative settlement amount of the grid unit and the predicted cumulative settlement amount of the adjacent grid;

[0187] is the standard inclination tolerance threshold value; is the standard settlement failure threshold value;

[0188] S33: Extract the inclination tolerance threshold value and the settlement failure threshold value of the device in S31 to dynamically replace and adjust the standard inclination tolerance threshold value and the standard settlement failure threshold value in the sensitivity index model;

[0189] It should be noted that the dynamic adjustment processing includes:

[0190] When the grid unit belongs to the main transformer area, that is, the sensitivity index model is adjusted by the main transformer inclination tolerance threshold value, and the acquisition strategy of the main transformer inclination tolerance threshold value includes:

[0191] ;

[0192] wherein, is the basic inclination tolerance under the rated load of the main transformer;

[0193] Exemplarily, in the embodiment, the initial value of the main transformer inclination tolerance threshold value is 0.5°;

[0194] The winding mechanical relaxation coefficient is denoted as K;

[0195] Exemplarily, in the embodiment, the winding mechanical relaxation coefficient K is determined by the equipment mechanical characteristic test, and the value is 0.1-0.3.

[0196] The real-time load current is denoted as I; The rated current is denoted as I0;

[0197] Exemplarily, in the embodiment, it is to be explained that the higher the load of the main transformer area equipment is, that is, the larger the load current I is, the larger the winding electromagnetic force of the equipment in the main transformer area is, and the lower the inclination tolerance of the foundation is, so the threshold value is dynamically reduced, for example, the threshold value is reduced to 0.3° when the load is full.

[0198] When the grid unit belongs to the GIS area, that is, the sensitivity index model is adjusted by a GIS inclination tolerance threshold value, and the GIS inclination tolerance threshold value is determined according to the following formula: The acquisition strategy of the GIS inclination tolerance threshold value includes:

[0199]

[0200] Wherein, the maximum allowable expansion of the bellows connected to the busbar of the GIS area equipment is denoted as Lmax.

[0201] L is the average value of the center distance of adjacent gas chambers of the GIS area equipment.

[0202] Exemplarily, in the embodiment, it is to be explained that the busbar connection of the GIS equipment usually adopts a sealed structure such as bellows, and the purpose is to compensate for the displacement and deformation that may be generated in the operation process of the equipment, so as to ensure the sealing performance. When the equipment is inclined, the bellows connected to the busbar will be stretched or compressed. If the inclination angle is too large and exceeds the maximum allowable expansion of the bellows, the bellows may be damaged, thereby affecting the sealing performance of the GIS area equipment, causing the internal insulating gas to leak. Therefore, the GIS inclination tolerance threshold value is determined according to the center distance of adjacent gas chambers and the maximum allowable expansion of the bellows, so as to ensure the sealing performance of the busbar connection of the GIS area equipment when the substation foundation subsides.

[0203] It is to be explained that the dynamic adjustment process further includes:

[0204] When the grid unit belongs to the main transformer area, that is, the sensitivity index model is adjusted by a main transformer subsidence failure threshold value, and the main transformer subsidence failure threshold value is determined according to the following formula: The acquisition strategy of the main transformer subsidence failure threshold value includes:

[0205] ;​​​​

[0206] wherein d is the maximum horizontal displacement allowed by the connecting part of the main transformer area equipment;

[0207] It is illustratively noted that the maximum horizontal displacement d allowed by the connecting part of the main transformer area equipment is generally determined according to the material properties, design specifications, etc. of the connecting part, and in the present embodiment, the value of d is 5 mm;

[0208] D is the base diameter of the main transformer area equipment; is the maximum inclination angle allowed by the base of the main transformer area equipment;

[0209] It is illustratively noted that, considering the structural strength and stability of the transformer in the factory state in the main transformer area, in the present embodiment, the value of the maximum inclination angle allowed by the base of the main transformer area equipment is 0.5°;

[0210] It is noted that the setting of the main transformer settlement failure threshold includes the limiting item of the foundation settlement on the connecting part and the limiting item of the structural stability of the transformer itself, and the minimum value between the two is taken as the main transformer settlement failure threshold Because as long as the differential settlement of the foundation reaches the smaller of the two values, it will pose a threat to the safe operation of the transformer.

[0211] It is noted that in the present embodiment, for the limiting item of the connecting part, if the differential settlement of the foundation causes the horizontal displacement of the transformer base to exceed the range that the connecting part can withstand, the connecting part may be subjected to excessive tensile force, shear force, etc., thereby causing damage to the connecting part, and further affecting the stability and safety of the transformer;

[0212] It is noted that in the present embodiment, for the limiting item of the structural stability of the transformer itself, if the foundation inclination angle is too large, the windings, iron core, etc. inside the transformer may be subjected to additional stress, affecting their normal operation, and even possibly causing damage to the components.

[0213] When the grid cell belongs to the GIS area, i.e. , the sensitivity index model is adjusted by the GIS settlement failure threshold, which is obtained by the following strategy:

[0214] ;

[0215] wherein, is the compression allowance of the sealing ring of the GIS area equipment;

[0216] is the length of a single section of the busbar; ​Allowing the bias angle for bus butt joint;

[0217] Exemplarily, in the embodiment, ;

[0218] Exemplarily, it should be noted that, for the GIS settlement failure threshold Comprising: the limiting item of sealing failure and the limiting item of bus butt joint bias angle, taking the minimum value between the two as the GIS settlement failure threshold Because as long as the foundation differential settlement exceeds one of the limiting items, it will have a serious impact on the allowance of GIS equipment;

[0219] It should be noted that, for the setting of the limiting item of sealing failure, the GIS equipment usually adopts a sealing structure to ensure the stability of the internal insulation and gas environment, and the sealing ring is the key component to realize sealing. If the compression allowance is too small, it may cause sealing failure, internal gas leakage, and affect the normal operation of the equipment;

[0220] It should be noted that, for the setting of the limiting item of bus butt joint bias angle, considering that the bus in the GIS equipment is used to connect various electrical elements, the bias angle at the bus butt joint has a certain allowable range, but if the settlement difference is too large, it will cause the bus butt joint bias angle to exceed the allowable value, which will cause poor contact of the bus connection part, partial discharge and other problems, and even cause electrical failure in severe cases.

[0221] In S33, the dynamic adjustment process includes:

[0222] When the grid unit belongs to the main transformer area, that is, The sensitivity index model is dynamically adjusted by the main transformer tilt tolerance threshold and the main transformer settlement failure threshold;

[0223] When the grid unit belongs to the GIS area, that is, The sensitivity index model is dynamically adjusted by the GIS tilt tolerance threshold and the GIS settlement failure threshold;

[0224] When the grid unit belongs to the cable trench, that is, The dynamic adjustment of the sensitivity index model includes:

[0225] Collecting the operation data of the cable terminal head in the grid unit, the parameters of the cable terminal head including: the differential settlement amount of the foundation at both ends of the terminal head and the real-time temperature difference at both ends of the terminal head;

[0226] Exemplarily, in the embodiment, the real-time operation temperature of the cable is obtained through the temperature measuring optical fiber;

[0227] The collected operation data of the cable terminal head is imported into the coupling stress calculation strategy to calculate the real-time coupling stress of the equipment in the cable trench.

[0228] It should be noted that the coupling stress of the cable trench equipment is caused by thermal expansion and settlement;

[0229] Exemplarily, in the embodiment, a calculation strategy of real-time coupling stress of cable trench equipment is provided, in particular:

[0230]

[0231] Among them, is the real-time coupling stress of the cable trench equipment;

[0232] is the difference between the foundation settlement of the two ends of the terminal head;

[0233] is the length of the cable terminal head; is the thermal expansion coefficient of the cable; is the real-time temperature difference between the two ends of the terminal head; is the elastic modulus of the cross-linked polyethylene cable;

[0234] The real-time coupling stress of the cable trench equipment is compared with the maximum allowable stress of the cable trench equipment, when the real-time coupling stress is greater than the maximum allowable stress, the difference between the foundation settlement of the two ends of the terminal head at this time is taken as the cable settlement failure threshold; when the real-time coupling stress is less than or equal to the maximum allowable stress, the maximum settlement difference allowed in the design of the cable in the factory state is taken as the cable settlement failure threshold;

[0235] According to the cable settlement failure threshold, the sensitivity index model is dynamically adjusted.

[0236] Exemplarily, in the embodiment, it should be noted that the cable terminal head and other cable trench equipment are usually fixed in a specific position during installation, and are closely connected with the ground or support, and generally will not be obviously inclined due to external factors;

[0237] The main potential risk comes from the stress change of the cable caused by factors such as ground settlement, rather than the influence of inclination, which includes the tension of the cable itself, thermal expansion force, and shear force caused by ground settlement, etc. Settlement will cause tensile or compressive stress at the terminal head of the cable, which will cause damage to the cable when the stress exceeds the allowable stress, affecting its insulation performance and electrical performance, and even leading to failure. For example, when uneven settlement occurs in the cable trench, the stress at the cable terminal head will be concentrated, which may cause problems such as insulation layer rupture and conductor connection loosening;

[0238] Therefore, as described above, in the embodiment, when the grid unit belongs to the cable trench, that is, , the equipment inclination of the cable trench equipment is 0 by default.​

[0239] S34: Output the real-time sensitivity index of each grid unit by adjusting the sensitivity index model through dynamic replacement.

[0240] S4: Construct a dual risk propagation network, calculate the deposition risk probability value and global risk entropy value based on the real-time sensitivity index of the equipment, and generate a three-dimensional visual maintenance navigation.

[0241] S41: Obtain the equipment line transmission capacity of each grid unit in the substation and the total system capacity, and calculate the electrical weight of each grid unit, wherein the calculation strategy of the electrical weight is the ratio of the equipment line transmission capacity to the total system capacity.

[0242] It should be noted that the greater the proportion of the equipment line transmission capacity of the grid unit, the more significant the impact of equipment failure on the substation, and the higher the risk propagation weight.

[0243] S42: Obtain the physical distance between devices in each grid unit, quantify the risk propagation weight of adjacent devices through a decay function, and obtain the structure weight.

[0244] Exemplarily, in the present embodiment, the calculation strategy of the structure weight is:

[0245] ;

[0246] wherein, is the distance threshold;

[0247] is the distance decay coefficient, is the physical distance between devices;

[0248] It should be noted that when , the structure weight tends to 1, and the propagation probability of the risk of adjacent devices in the substation is large.

[0249] When , the structure weight decays rapidly, and the influence of long-distance devices in the substation can be ignored.

[0250] S43: Construct a dual risk propagation network based on the electrical weight and the structure weight of the substation, wherein the dual risk propagation network is a risk propagation weight matrix of , wherein N is the total number of grid units in the substation, and the comprehensive weight in the risk propagation weight matrix is the sum of the electrical weight and the structure weight.

[0251] S44: Calculate the deposition risk probability value of each grid unit according to the real-time sensitivity index of the equipment and the risk propagation weight matrix.

[0252] Preferably, the settlement risk probability value of each grid cell The calculation strategy is as follows:

[0253] ;

[0254] in, Let i be the device real-time sensitivity index of the device in the i-th grid cell;

[0255] The comprehensive weight of the risk of a device in the i-th grid cell propagating to other grid cells;

[0256] For example, in this embodiment, it should be noted that the settlement risk probability value for each grid cell is... , Used to quantify the combined impact of equipment sensitivity and its risk propagation weight;

[0257] Used to quantify the overall risk value of a substation;

[0258] S45: Based on the settlement risk probability value, simultaneously calculate the global risk entropy value of the substation;

[0259] Preferably, the global risk entropy value The specific calculation strategy is as follows:

[0260] ;

[0261] For example, in this embodiment, it should be noted that when This indicates that the substation's settlement risk is highly concentrated, and the settlement risk is dominated by a few pieces of equipment;

[0262] when At that time, the substation shows a uniform distribution of settlement risk, requiring settlement maintenance for the entire substation;

[0263] S46: Arrange the settlement risk probability values ​​in descending order from high to low to generate a substation equipment settlement risk priority list. Simultaneously generate a three-dimensional visualization maintenance navigation for the substation based on the equipment settlement risk priority list. At the same time, use the global risk entropy value as an assessment indicator of the overall risk of the substation. When the global risk entropy value exceeds the preset risk entropy value, an alarm is triggered and the substation's global emergency plan is activated.

[0264] When the global risk entropy value does not exceed the preset risk entropy value, the prediction of the substation foundation settlement continues.

[0265] Example 2: Figure 2 As shown in the figure, the substation foundation settlement prediction and analysis system based on an industrial cloud platform according to an embodiment of the present invention is as follows:Figure 2 The method comprises the following modules:

[0266] The three-dimensional modeling module, the settlement quantification module, the sensitivity evaluation module, the risk evaluation module and the maintenance navigation module;

[0267] The three-dimensional modeling module is configured to establish a digital grid unit of a three-dimensional space of a substation, and associate the digital grid unit and geographic coordinates with basic engineering parameters.

[0268] The settlement quantification module is configured to collect real-time working condition data and underground water level data of all equipment in the substation, and predict real-time settlement rates and cumulative settlement amounts of each grid unit.

[0269] The sensitivity evaluation module is configured to dynamically adjust equipment inclination threshold values and settlement failure threshold values in a sensitivity index model according to the real-time working condition data, and output real-time sensitivity index values of the equipment through the sensitivity index model.

[0270] The risk evaluation module is configured to construct a dual risk propagation network, and calculate settlement risk probability values and global risk entropy values based on the real-time sensitivity index values of the equipment.

[0271] The maintenance navigation module is configured to generate a three-dimensional visual maintenance navigation according to an evaluation result of the risk evaluation module.

[0272] Embodiment three provides an electronic device, comprising a processor and a memory, wherein the memory stores a computer program that can be invoked by the processor.

[0273] The processor invokes the computer program stored in the memory to execute the above-mentioned substation foundation settlement prediction and analysis method based on an industrial cloud platform.

[0274] The electronic device can have great differences due to different configurations or performances, and can include one or more processors (Central Processing Units, CPUs) and one or more memories, wherein the memory stores at least one computer program, which is loaded and executed by the processor to implement the substation foundation settlement prediction and analysis method based on an industrial cloud platform provided by the above-mentioned method embodiments. The electronic device can also include other components for realizing device functions, for example, the electronic device can also have a wired or wireless network interface and an input and output interface, etc., so as to perform data input and output. This embodiment will not be described here.

[0275] Embodiment four provides a computer readable storage medium, which stores an erasable computer program.

[0276] When the computer program runs on the computer device, the computer device is caused to perform the above-mentioned substation foundation settlement prediction analysis method based on the industrial cloud platform.

[0277] For example, the computer readable storage medium can be a Read-Only Memory (ROM), a Random Access Memory (RAM), a Compact Disc Read-Only Memory (CD-ROM), a magnetic tape, a floppy disk, and an optical data storage device, etc.

[0278] It should be understood that the size of the sequence number of each process described above in various embodiments of the present application does not mean the order of execution, and the execution order of each process should be determined according to its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0279] It should be understood that determining B according to A does not mean that B is determined only according to A, but B can also be determined according to A and / or other information.

[0280] The above-mentioned embodiments can be realized all or partially by software, hardware, firmware or any combination thereof. When realized by software, the above-mentioned embodiments can be realized in the form of a computer program product all or partially. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the flow or function according to the embodiments of the present application is generated all or partially. The computer can be a general-purpose computer, a special-purpose computer, a computer network or other programmable device. The computer instructions can be stored in a computer readable storage medium or transferred from one computer readable storage medium to another, for example, the computer instructions can be transferred from one website, computer, server or data center to another website, computer, server or data center through a wired network or / and wireless network. The computer readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. containing one or more available medium sets. The available medium can be a magnetic medium (for example, floppy disk, hard disk, magnetic tape), an optical medium (for example, DVD) or a semiconductor medium. The semiconductor medium can be a solid state disk.

[0281] Those skilled in the art can clearly understand that the units and algorithm steps of each example described in combination with the embodiments disclosed in the present application can be realized by electronic hardware or a combination of computer software and electronic hardware. Whether the functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0282] Those skilled in the art can clearly understand that, for the convenience and brevity of the description, the specific working processes of the above-described system, device and unit can refer to the corresponding processes in the foregoing method embodiments, which will not be repeated here.

[0283] In several embodiments provided by the present application, it should be understood that the disclosed system, device and method can be implemented in other ways. For example, the device embodiments described above are only schematic. The division of the units is only one, and actual implementation can have another division manner, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units shown or discussed can be indirect coupling or communication connection through some interface, device or unit, which can be electrical, mechanical or other form.

[0284] The units described as separate components can or can not be physically separate, and the components shown as units can or can not be physical units, that is, they can be located in one place, or they can be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the embodiment.

[0285] In addition, each functional unit in each embodiment of the present application can be integrated into a processing unit, or each unit can exist physically, or two or more units can be integrated into one unit.

[0286] In the description of the present specification, the description of the terms "one embodiment", "example", "specific example" and the like means that the specific features, structures, materials or characteristics described in combination with the embodiment or example are included in at least one embodiment or example of the present application. In the present specification, the illustrative description of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0287] The above shows and describes the basic principles and main features of the present application and the advantages of the present application. Those skilled in the art should understand that the present application is not limited to the above embodiments, and the above embodiments and descriptions in the specification are only to illustrate the principles of the present application. Without departing from the spirit and scope of the present application, various changes and improvements can be made to the present application, and these changes and improvements all fall within the scope of the claimed present application. The scope of protection of the present application is defined by the appended claims and their equivalents.

Claims

1. A method for predicting and analyzing substation foundation settlement based on an industrial cloud platform, characterized in that, The method includes: S1: Establish digital grid cells in the three-dimensional space of the substation and associate the digital grid cells and geographic coordinates with basic engineering parameters; S2: Collect real-time operating data and groundwater level data of all equipment in the substation, and predict the real-time settlement rate and cumulative settlement of each grid cell; S3: Dynamically adjust the standard tilt tolerance threshold and standard settlement failure threshold in the sensitivity index model based on real-time operating data, and output the real-time sensitivity index of the equipment through the sensitivity index model; S3 includes the following specific steps: S31: Based on the real-time operating status of the equipment in each grid cell, establish tilt tolerance thresholds and settlement failure thresholds that vary with the operating conditions of the equipment in the grid cell. S32: Establish a sensitivity index model and determine the device sensitivity weight of each grid cell using the hierarchical analysis algorithm. Specifically, the sensitivity index model is as follows: ； in, For the equipment settlement sensitivity of each grid unit; For device sensitivity weights; The device tilt angle is obtained through actual measurement using a sensor network; This is the average of the difference in settlement between the predicted cumulative settlement of the grid cell and the predicted cumulative settlement of the neighboring grid cells; The standard tilt tolerance threshold; The standard settlement failure threshold; S33: Extract the tilt tolerance threshold and settlement failure threshold of the equipment in S31 and dynamically replace and adjust the standard tilt tolerance threshold and standard settlement failure threshold in the sensitivity index model; S34: Output the real-time device sensitivity index of each grid cell by dynamically replacing and adjusting the sensitivity index model; S4: Construct a dual risk propagation network, calculate the probability value of settlement risk and the global risk entropy value based on the real-time sensitivity index of the equipment, and generate a three-dimensional visual maintenance navigation.

2. The substation foundation settlement prediction and analysis method based on an industrial cloud platform according to claim 1, characterized in that, S2 include: S21: Extract the regional function codes and real-time operation data of the devices in the grid cells; S22: Establish a dynamic load quantification model for equipment, and input real-time operating data into the dynamic load quantification model for equipment according to the regional function code, and output the dynamic load data of each grid unit, wherein the dynamic load data includes: dynamic load of the main transformer area and dynamic load of the GIS area. S23: Real-time monitoring of groundwater level data in each grid cell, and determination of baseline settlement rate of each grid cell based on groundwater level data; S24: Extract dynamic load data and calculate the combined additional stress between devices in the mesh element.

3. The method for predicting and analyzing substation foundation settlement based on an industrial cloud platform according to claim 2, characterized in that, S2 also includes the following steps: S25: Calculate the corrected real-time settlement rate based on S23-S24; S26: Calculate the cumulative settlement of each grid cell based on the real-time settlement rate corrected for the grid cells.

4. The method for predicting and analyzing substation foundation settlement based on an industrial cloud platform according to claim 3, characterized in that, In S33, the dynamic adjustment process includes: When the grid cell belongs to the main variable region, that is At that time, the sensitivity index model is dynamically adjusted by the main transformer tilt tolerance threshold and the main transformer settlement failure threshold; When the grid cell belongs to the GIS area, that is At that time, the sensitivity index model is dynamically adjusted by using the GIS tilt tolerance threshold and the GIS settlement failure threshold; When the grid cell belongs to the cable trench, that is The dynamic adjustment of the sensitivity index model includes: The operation data of the cable terminal head in the grid cell is collected. The parameters of the cable terminal head include: the difference in foundation settlement at both ends of the terminal head and the real-time temperature difference at both ends of the terminal head. The collected operating data of the cable terminal head is imported into the coupling stress calculation strategy to calculate the real-time coupling stress of the equipment in the cable trench. The real-time coupled stress of the equipment in the cable trench is compared with the maximum allowable stress of the equipment in the cable trench. When the real-time coupled stress is greater than the maximum allowable stress, the difference in the settlement of the foundations at both ends of the terminal head at this time is taken as the cable settlement failure threshold. When the real-time coupled stress is less than or equal to the maximum allowable stress, the maximum allowable settlement difference under the design conditions of the cable at the factory is taken as the cable settlement failure threshold. The sensitivity index model is dynamically adjusted based on the cable settlement failure threshold. in, Encode the regional functions of devices in the grid cell.

5. The substation foundation settlement prediction and analysis method based on an industrial cloud platform according to claim 4, characterized in that, S4 include: S41: Obtain the equipment line transmission capacity and total system capacity of each grid unit in the substation, and calculate the electrical weight of each grid unit, wherein the calculation strategy of the electrical weight is the ratio of equipment line transmission capacity to total system capacity; S42: Obtain the physical distance between devices in each grid cell, quantify the risk propagation weight of neighboring devices through the attenuation function, and obtain the structural weight; S43: Construct a dual risk propagation network based on the electrical and structural weights of the substation. The dual risk propagation network is... The risk propagation weight matrix is ​​given by N, where N is the total number of grid cells in the substation, and the comprehensive weight in the risk propagation weight matrix is ​​the sum of the electrical weight and the structural weight.

6. The method for predicting and analyzing substation foundation settlement based on an industrial cloud platform according to claim 5, characterized in that, S4 also includes: S44: Calculate and obtain the settlement risk probability value of each grid unit based on the equipment real-time sensitivity index and risk propagation weight matrix; S45: Based on the settlement risk probability value, simultaneously calculate the global risk entropy value of the substation; S46: Arrange the settlement risk probability values ​​in descending order from high to low to generate a settling risk priority list for equipment in the substation. Simultaneously generate a 3D visualization maintenance navigation for the substation based on the settling risk priority list. At the same time, use the global risk entropy value as an assessment indicator of the overall risk of the substation. When the global risk entropy value exceeds the preset risk entropy value, an alarm is triggered. When the global risk entropy value does not exceed the preset risk entropy value, the prediction of the substation foundation settlement continues.

7. A substation foundation settlement prediction and analysis system based on an industrial cloud platform, used to implement the substation foundation settlement prediction and analysis method based on an industrial cloud platform as described in any one of claims 1-6, characterized in that, The system includes: The system includes a 3D modeling module, a settlement quantification module, a sensitivity assessment module, a risk assessment module, and a maintenance navigation module. The 3D modeling module is used to establish digital grid cells in the 3D space of the substation and associate the digital grid cells and geographic coordinates with basic engineering parameters; The settlement quantification module is used to collect real-time operating data and groundwater level data of all equipment in the substation, and predict the real-time settlement rate and cumulative settlement of each grid unit. The sensitivity assessment module dynamically adjusts the standard tilt tolerance threshold and standard settlement failure threshold in the sensitivity index model based on real-time operating data, and outputs the real-time sensitivity index of the equipment through the sensitivity index model. The risk assessment module is used to construct a dual risk propagation network, and calculates the subsidence risk probability value and the global risk entropy value based on the real-time sensitivity index of the equipment. The maintenance navigation module generates a three-dimensional visual maintenance navigation based on the assessment results of the risk assessment module.

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