Goods pile data real-time updating method based on dynamic surveying and mapping and temperature inspection

Abstract

The invention discloses a real-time stack data updating method based on dynamic surveying and mapping and temperature inspection, which comprises the following steps of: recording a track around the edge of a stack by adopting an RTK (Real-Time Kinematic) positioning technology, and generating a real-time stack type track diagram of the stack; a temperature measuring rod is adopted to carry out multiple times of temperature measurement at different depths in different directions of the goods pile, and the spatial positioning of a temperature measuring point is recorded; fitting the real-time stack type trajectory diagram of the stack based on a stack type reconstruction module in a data fusion engine to obtain a three-dimensional stack model; based on a temperature field mapping module in the data fusion engine, positioning the space of the temperature measurement point in the three-dimensional cargo pile model for fusion, and updating to obtain a real-time cargo pile temperature gradient thermodynamic diagram; comparing the temperature of each area in the goods pile temperature gradient thermodynamic diagram with a corresponding temperature threshold, judging whether the goods pile temperature reaches a high-temperature early warning or not, and if yes, triggering a mobile terminal to give an alarm; and minute-level updating of the three-dimensional cargo pile model and the real-time cargo pile temperature gradient thermodynamic diagram is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of yard measurement, and in particular to a cargo pile data real-time updating method based on dynamic mapping and temperature inspection. BACKGROUND

[0002] Traditional port cargo pile data collection relies on manual recording and offline mapping, and temperature measurement uses handheld devices for single-point entry. The existing scheme has two major defects: pile type update lag, the shape change after cargo loading and unloading needs to be re-mapped, which takes more than 2 hours per time and cannot be synchronized to the system in real time; temperature data island, manual temperature measurement records and pile type map are separated and cannot be associated with spatial position to analyze temperature distribution. Meanwhile, there are the following technical problems: low efficiency, manual mapping around the pile takes an average of 30 minutes per pile, and the daily update rate of large yards is less than 40%; data fragmentation, pile type map and temperature data are stored in independent systems and cannot be fused and analyzed, for example, the shape of the high-temperature area; safety risk, personnel need to work close to the cargo pile, which may cause accidents when collapsing or high temperature; path redundancy, temperature measurement points are not dynamically planned, and the repeated path ratio is more than 50%. SUMMARY

[0003] The present application provides a cargo pile data real-time updating method based on dynamic mapping and temperature inspection, which realizes minute-level updating of three-dimensional cargo pile model and temperature field by fusing the data of RTK positioning card dynamic mapping cargo pile trajectory and temperature measurement rod.

[0004] Technical scheme: To achieve the above purpose, the cargo pile data real-time updating method based on dynamic mapping and temperature inspection of the present application comprises the following steps:

[0005] S1, using RTK positioning technology to record the trajectory around the edge of the cargo pile, and generating a real-time pile type trajectory map of the cargo pile;

[0006] S2, using a temperature measurement rod to measure temperature at different depths in different directions of the cargo pile, and recording the temperature and spatial positioning of the temperature measurement points;

[0007] S3, fitting the real-time pile type trajectory map of the cargo pile based on the pile type reconstruction module in the data fusion engine to obtain a three-dimensional cargo pile model;

[0008] S4, based on the temperature field mapping module in the data fusion engine, fusing the temperature and spatial positioning of the temperature measurement points with the three-dimensional cargo pile model to update a real-time cargo pile temperature gradient thermal map;

[0009] S5, comparing the temperature of each region in the cargo pile temperature gradient thermal map with its corresponding temperature threshold value to determine whether the cargo pile temperature reaches the high-temperature early warning, and if so, triggering the mobile terminal alarm.

[0010] Further, in the step S1, the RTK positioning technology realizes centimeter-level positioning through the cooperation of the reference station and the rover station to generate the pile edge trajectory; the reference station and the rover station synchronously observe satellite signals, the reference station calculates the error between the carrier phase observation value and the theoretical value according to the observed satellite signals to generate the differential correction data; the rover station eliminates common errors through the double-difference observation model according to the received satellite signals and the differential correction data to obtain the RTK positioning card trajectory point, and realizes the accurate positioning of the RTK positioning card; the obtained RTK positioning card trajectory point set is taken as the real-time pile shape trajectory map of the pile, as shown below:

[0011]

[0012] In the formula, Pn is the trajectory point of the nth RTK positioning card, x n , y n , and z n are three-dimensional coordinate points of the trajectory point of the nth RTK positioning card on three-dimensional coordinate axes respectively.

[0013] Further, in the step S2, the temperature measuring rod is used to measure the temperature in different directions of the pile for multiple times at different depths, and the spatial positioning of the temperature measuring point is recorded; including the following steps:

[0014] S1-1, obtaining the number of bare surfaces of the pile and the size of the pile based on the real-time pile shape trajectory map of the pile;

[0015] S1-2, setting the number of temperature measuring points of each bare surface of the pile, the temperature measuring depth, and the temperature measuring times of each temperature measuring point according to the size of the pile and the number of bare surfaces;

[0016] S1-3, setting the specific temperature measuring position of each bare surface according to the number of temperature measuring points of each bare surface and the temperature measuring depth;

[0017] S1-4, inserting the temperature measuring rod into the pile for multiple temperature measurements according to the temperature measuring depth of each bare surface and the specific temperature measuring position of each bare surface, and recording the temperature and spatial positioning of the temperature measuring point at this time.

[0018] Further, the number C of temperature measuring points of each bare surface is calculated through the size of the pile and the number of bare surfaces of the pile, and the calculation process is as follows:

[0019]

[0020] In the formula, C is the number of temperature measuring points of each bare surface, M G is the number of bare surfaces of the pile, and M Dis a size grade coefficient of the cargo pile, the size grade of the cargo pile is divided into small, medium, large and super large; a and β are respectively the number of the bare leakage surface of the cargo pile and the weight coefficient of the size of the cargo pile; ε is a compensation coefficient; and round is an integral operation.

[0021] Further, the depth of temperature measurement of each bare leakage surface is divided into shallow layer temperature measurement and deep layer temperature measurement, and the selection of the temperature measurement depth of each bare leakage surface is set according to the size grade of the cargo pile; when the size grade of the cargo pile is small, the temperature measurement depth of each bare leakage surface is shallow layer temperature measurement; when the size grade of the cargo pile is medium, the temperature measurement depth of each bare leakage surface at least contains deep layer temperature measurement of one temperature measurement point, and the rest of the temperature measurement points are shallow layer temperature measurement; when the size grade of the cargo pile is large, the temperature measurement depth of each bare leakage surface at least contains deep layer temperature measurement of two temperature measurement points, and the rest of the temperature measurement points are shallow layer temperature measurement; when the size grade of the cargo pile is super large, the temperature measurement depth of each bare leakage surface at least contains deep layer temperature measurement of three temperature measurement points, and the rest of the temperature measurement points are shallow layer temperature measurement.

[0022] Further, in the step S1-3, the specific temperature measurement position of each bare leakage surface is set according to the number of the temperature measurement points and the temperature measurement depth of each bare leakage surface; when each bare leakage surface does not contain a temperature measurement point of deep layer temperature measurement, the temperature measurement positions of each bare leakage surface are uniformly distributed around the center point of the bare leakage surface, and the distance between each temperature measurement position and the center point of the bare leakage surface is determined according to the number of the temperature measurement points; the number of the temperature measurement points of each bare leakage surface is divided into four intervals; when the number of the temperature measurement points of each bare leakage surface is in the first interval, the distance between each temperature measurement position and the center point of the bare leakage surface is S A ; when the number of the temperature measurement points of each bare leakage surface is in the second interval, the distance between each temperature measurement position and the center point of the bare leakage surface is S B ; when the number of the temperature measurement points of each bare leakage surface is in the third interval, the distance between each temperature measurement position and the center point of the bare leakage surface is S C ; when the number of the temperature measurement points of each bare leakage surface is in the fourth interval, the distance between each temperature measurement position and the center point of the bare leakage surface is S D ; and the number of the temperature measurement points of the first interval to the fourth interval increases in turn, .

[0023] Further, when each bare leakage surface contains deep temperature measurement points, each bare leakage surface is divided into a central region and a peripheral region; the central region is a circular region with the center point of each bare leakage surface as the center, and occupies 1 / 3 of the area of each bare leakage surface; the area of each bare leakage surface excluding the central region is the peripheral region; the deep temperature measurement positions are all set in the central region, and the deep temperature measurement positions are uniformly distributed in the central region; the shallow temperature measurement positions are all set in the peripheral region, and the shallow temperature measurement positions are uniformly distributed around the central region, and the distance from each shallow temperature measurement position to the edge of the central region is S T .

[0024] Further, in step S3, the stack type re-module fits the real-time stack trajectory map of the cargo stack into a three-dimensional cargo stack model. First, the trajectory point set of the RTK positioning card is filtered by point cloud filtering to remove drift points. The trajectory point set of the filtered RTK positioning card is extracted by a convex hull based on an Alpha-Shape algorithm to generate a stack boundary. A non-uniform rational B-spline (NURBS) is used for surface fitting based on the stack boundary to construct a continuous surface and obtain a three-dimensional cargo stack model.

[0025]

[0026] In the formula, N i,p is a rational B-spline (NURBS) basis function, ω i,j is a weight, and P i,j is a control point of the three-dimensional cargo stack model.

[0027] Further, in step S4, the temperature and spatial positioning of the temperature measurement points are fused with the three-dimensional cargo stack model to update a real-time stack temperature gradient thermal map. The position of the temperature measurement points in the three-dimensional cargo stack model is calculated through GPS coordinates and offset to realize the fusion of spatial positioning, and the calculation process is as follows:

[0028]

[0029] In the formula, Ptemp is the actual position of the temperature measurement point in the three-dimensional cargo stack model coordinate system, P GPS is the GPS coordinate recorded by the temperature measurement point, is the on-site coordinate offset;

[0030] A temperature interpolation algorithm and an inverse distance weighting method are used, and a continuous temperature field is generated based on the weighted adjacent temperature measurement points to obtain a real-time stack temperature gradient thermal map. Let the grid vertex be (x, y), and n temperature measurement points are known. The interpolation temperature T(x, y) is calculated, and the calculation process is as follows:

[0031]

[0032] wherein k is an attenuation factor, d i is the distance from the grid point to the temperature measuring point;

[0033] The temperature difference approximation gradient of the adjacent vertex of each grid vertex (x, y) is adopted, and a continuous temperature field is generated by gradient calculation, and then a real-time cargo pile temperature gradient heat map is obtained; the calculation formula is as shown below:

[0034]

[0035] wherein, , , is the size of the grid unit.

[0036] Beneficial effects: the cargo pile data real-time updating method based on dynamic mapping and temperature inspection of the application realizes minute-level updating of the three-dimensional cargo pile model and the temperature field through the fusion of the RTK positioning card dynamic mapping cargo pile trajectory and the data of the temperature measuring rod; solves the problems of cargo pile data updating delay, low efficiency of manual mapping, and separation of temperature and pile type data; the single cargo pile mapping time is shortened from 30 minutes to 5 minutes, so that the pile type map updating delay of the cargo pile is reduced from hour level to minute level; the spatial correlation accuracy of the temperature field and the three-dimensional cargo pile model reaches 95%, supports high-temperature area shape analysis, and automatically generates a temperature gradient warning map; the dangerous recognition rate of steep slope, high temperature and other cargo piles is 100%, and the accident rate is reduced by 90%; the investment in special mapping equipment is reduced by 70%, and the labor cost is reduced by 40%. BRIEF DESCRIPTION OF DRAWINGS

[0037] Figure 1 is a flowchart of the cargo pile data real-time updating method based on dynamic mapping and temperature inspection. DETAILED DESCRIPTION

[0038] The application will be further described below in combination with the drawings.

[0039] As shown in Figure 1 , the cargo pile data real-time updating method based on dynamic mapping and temperature inspection comprises the following steps:

[0040] S1, using RTK positioning technology to record the trajectory around the edge of the cargo pile, and generating a real-time pile type trajectory map of the cargo pile;

[0041] S2, using a temperature measuring rod to measure temperature in different directions of the cargo pile for multiple times at different depths, and recording the temperature and spatial positioning of the temperature measuring point;

[0042] S3, fitting the real-time pile type trajectory map of the cargo pile based on the pile type reconstruction module in the data fusion engine, to obtain a three-dimensional cargo pile model;

[0043] S4, based on the temperature field mapping module in the data fusion engine, the temperature and spatial positioning of the temperature measurement points are fused with the three-dimensional cargo stack model, the temperature value and spatial positioning of each temperature measurement point are corresponded with the specific position thereof in the three-dimensional cargo stack model, and then a continuous temperature field is generated inside the model, and a real-time cargo stack temperature gradient thermal map is obtained by updating;

[0044] S5, comparing the temperature of each region in the cargo stack temperature gradient thermal map with the corresponding temperature threshold value, judging whether the cargo stack temperature reaches the high temperature early warning, and if so, triggering the mobile terminal alarm.

[0045] In the step S1, the RTK positioning technology realizes centimeter-level positioning through the cooperation of the reference station and the flow station, and generates the cargo stack edge trajectory; the reference station and the flow station synchronously observe satellite signals, the reference station calculates the error between the carrier phase observation value and the theoretical value according to the observed satellite signals, generates difference correction data; the flow station eliminates common errors by a double-difference observation model according to the received satellite signals and difference correction data to obtain the trajectory points of the RTK positioning card, and realizes accurate positioning of the RTK positioning card; wherein the calculation process of the flow station eliminating common errors by the double-difference observation model according to the received satellite signals and difference correction data is as follows:

[0046]

[0047] In the formula, is the double-difference carrier phase observation value, is the geometric distance difference, is the integer ambiguity difference, λ is the wavelength, ε is the noise, and the RTK positioning card is the flow station.

[0048] The RTK positioning card surrounds the cargo stack edge once, and the RTK positioning card automatically records the coordinates of the trajectory points, and the sampling frequency is 1Hz; the trajectory point set of the RTK positioning card obtained is obtained as the real-time stack type trajectory map of the cargo stack, as follows:

[0049]

[0050] In the formula, Pn is the trajectory point of the nth RTK positioning card, x n , y n , z n are three-dimensional coordinate points of the trajectory point of the nth RTK positioning card on three-dimensional coordinate axes.

[0051] In the step S2, the temperature measurement rod is used to measure the temperature in different directions of the cargo stack for multiple times at different depths, and the spatial positioning of the temperature measurement points is recorded; including the following steps:

[0052] S1-1, based on the real-time stack type trajectory of the cargo stack, the number of bare exposed surfaces of the cargo stack and the size of the cargo stack are obtained;

[0053] S1-2, according to the size of the cargo stack and the number of bare exposed surfaces, the number of temperature measurement points of each bare exposed surface of the cargo stack, the temperature measurement depth, and the temperature measurement times of each temperature measurement point are set;

[0054] S1-3, according to the number of temperature measurement points and the temperature measurement depth of each bare exposed surface, the specific temperature measurement position of each bare exposed surface is set;

[0055] S1-4, according to the temperature measurement depth of each bare exposed surface and the specific temperature measurement position of each bare exposed surface, the temperature measurement rod is inserted into the cargo stack for multiple temperature measurements, and the temperature and spatial positioning of the temperature measurement point are recorded at this time.

[0056] The number C of temperature measurement points of each bare exposed surface is calculated by the size of the cargo stack and the number of bare exposed surfaces of the cargo stack, and the calculation process is as follows:

[0057]

[0058] In the formula, C is the number of temperature measurement points of each bare exposed surface, M G is the number of bare exposed surfaces of the cargo stack, M D is the size level coefficient of the cargo stack, the size level of the cargo stack is divided into small, medium, large and super large, and each size level of the cargo stack corresponds to a size level coefficient, for example, the size level coefficients of small, medium, large and super large cargo stacks can be 1, 3, 5 and 7; α and β are the weight coefficients of the number of bare exposed surfaces of the cargo stack and the size of the cargo stack, respectively, and the weight coefficients are set according to the size level of the cargo stack, each size level of the cargo stack has its corresponding weight coefficient, and the setting of the weight coefficient can be adjusted according to the situation; ε is a compensation coefficient, which is set according to the type of goods in the cargo stack and the stacking method of the cargo stack; round is the rounding operation, which is the rounding operation of four or five.

[0059] The temperature measurement depth of each bare exposed surface is divided into shallow layer temperature measurement and deep layer temperature measurement, and the temperature measurement depth of each bare exposed surface is selected according to the size grade of the cargo pile; when the size grade of the cargo pile is small, the temperature measurement depth of each bare exposed surface is shallow layer temperature measurement; when the size grade of the cargo pile is medium, the temperature measurement depth of each bare exposed surface at least includes deep layer temperature measurement of one temperature measurement point, and the remaining temperature measurement points are shallow layer temperature measurement; when the size grade of the cargo pile is large, the temperature measurement depth of each bare exposed surface at least includes deep layer temperature measurement of two temperature measurement points, and the remaining temperature measurement points are shallow layer temperature measurement; when the size grade of the cargo pile is super large, the temperature measurement depth of each bare exposed surface at least includes deep layer temperature measurement of three temperature measurement points, and the remaining temperature measurement points are shallow layer temperature measurement. The temperature measurement depth of shallow layer temperature measurement and deep layer temperature measurement can be adjusted according to the size of the cargo pile and the number of bare exposed surfaces to obtain the most suitable temperature, and the formula for calculating the temperature measurement depth is as follows:

[0060]

[0061] In the formula, D represents the calculated temperature measurement depth; D0 represents the reference temperature measurement depth, which is fixed at 30 cm; k is a bare exposed surface coefficient, which is determined according to the number N of bare exposed surfaces, when N<=3, k=1.3C, when 5<=N<=8, k=1, and when N>=9, k=0.7. C L is a grade compensation value, which changes with the size grade L of the cargo pile, when the size grade of the cargo pile is small, L=1, C L =30; when the size grade of the cargo pile is medium, L=2, C L =50; when the size grade of the cargo pile is large, L=3, C L =80; and when the size grade of the cargo pile is super large, L=4, C L =100. The indication function: when type=D, it is deep layer temperature measurement, and the value is 1; when type≠D, it is shallow layer temperature measurement, and the value is 0.

[0062] In the step S1-3, the specific temperature measurement positions of each bare exposed surface are set according to the number of temperature measurement points and the temperature measurement depth of each bare exposed surface; when each bare exposed surface does not include a temperature measurement point of deep layer temperature measurement, the temperature measurement positions of each bare exposed surface are uniformly distributed around the center point of the bare exposed surface, and the distance between each temperature measurement position and the center point of the bare exposed surface is determined according to the number of temperature measurement points; the number of temperature measurement points of each bare exposed surface is divided into four intervals; when the number of temperature measurement points of each bare exposed surface is in the first interval, the distance between each temperature measurement position and the center point of the bare exposed surface is S A ; when the number of temperature measurement points of each bare exposed surface is in the second interval, the distance between each temperature measurement position and the center point of the bare exposed surface is S B ; when the number of temperature measurement points of each bare exposed surface is in the third interval, the distance between each temperature measurement position and the center point of the bare exposed surface is S C; when the number of temperature measurement points of each bare surface is in the fourth interval, the distance between each temperature measurement position and the center point of the bare surface is S D ; and the number of temperature measurement points in the first to fourth intervals increases in turn, for example, the number of temperature measurement points in the first interval is 1-3, the number of temperature measurement points in the second interval is 3-5, the number of temperature measurement points in the third interval is 5-7, and the number of temperature measurement points in the fourth interval is 7-10; the distance S D is greater than the distance S C , the distance S C is greater than the distance S B , the distance S B is greater than the distance S A , . The temperature measurement positions of each bare surface are uniformly distributed around the center point of the bare surface, and at this time the temperature measurement positions form an approximate circle with the center point of the bare surface as the center.

[0063] When each bare surface contains deep temperature measurement points, each bare surface is divided into a central region and a peripheral region; the central region is a circular region with the center point of each bare surface as the center, and occupies 1 / 3 of the area of each bare surface; the region of each bare surface excluding the central region is the peripheral region; the deep temperature measurement positions are all set in the central region, and the deep temperature measurement positions are uniformly distributed in the central region; the shallow temperature measurement positions are all set in the peripheral region, and the shallow temperature measurement positions are uniformly distributed around the central region, and the distance from each shallow temperature measurement position to the edge of the central region is S T . The deep temperature measurement positions can perform deep temperature measurement while performing shallow temperature measurement; while the shallow temperature measurement positions can only be used for shallow temperature measurement.

[0064] The deep temperature measurement positions are uniformly distributed in the central region, for example, when the deep temperature measurement position is one, the deep temperature measurement position can be the center point of the central region; when the deep temperature measurement position is two, the two deep temperature measurement positions can be located on both sides of the center point of the central region, and the distance from the temperature measurement position to the center point is the same as the distance from the temperature measurement position to the edge of the central region; when the deep temperature measurement position is three or more, the multiple deep temperature measurement positions are uniformly distributed around the center point, and the distance from each temperature measurement position to the center point is the same as the distance from the temperature measurement position to the edge of the central region, and the distance between each temperature measurement position and the adjacent temperature measurement position is the same.

[0065] The number of temperature measurement points, the temperature measurement depth and the temperature measurement times of each temperature measurement point are set according to the naked exposed surface of the cargo pile and the size grade of the cargo pile, so that the temperature of the cargo pile can be measured in all directions, and the temperature of each position of the cargo pile can be detected. The temperature and spatial positioning measured subsequently are fused with the three-dimensional cargo pile model to update the real-time cargo pile temperature gradient thermal map more accurately. By limiting the temperature measurement position of each naked exposed surface, more comprehensive temperature is collected, more comprehensive and accurate temperature data is provided for the subsequent weighted continuous temperature field, so that the generated continuous temperature field is smoother and more accurate.

[0066] In the step S3, the stack type reconfiguration module fits the real-time cargo pile trajectory map into a three-dimensional cargo pile model. Firstly, the trajectory point set of the RTK positioning card is subjected to point cloud filtering, and drift points are removed, for example, points with a height mutation greater than 50 cm or abnormal speed points are removed. The abnormal points with height mutation are removed. Firstly, the height difference between adjacent trajectory points is calculated, for example, the height difference between the i-th trajectory point and the i-1-th trajectory point is calculated , that is, the height difference between the i-th trajectory point and the previous trajectory point is calculated, and the calculation process is as follows:

[0067]

[0068] In the formula, Z i is the height of the i-th trajectory point, Z i-1 is the height of the i-1-th trajectory point; secondly, a threshold is set, and the threshold is set to 50 cm according to experience; when the calculated height difference is greater than the threshold 50, the i-th trajectory point is an abnormal point, and the i-th trajectory point is removed; when the calculated height difference is not greater than the threshold 50, the i-th trajectory point is not an abnormal point.

[0069] The speed abnormal point is removed. Firstly, the speed of each trajectory point moving to the next trajectory point is calculated according to the formula. The three-dimensional coordinates (X i , Y i , Z i ) and (X i-1 , Y i-1 , Z i-1 ) of adjacent two trajectory points and the corresponding sampling time stamps t i and t i-1 , t i and t i-1 are known, and the unit of t i is second. The instantaneous speed vector V i is calculated as follows:

[0070]

[0071] The calculated instantaneous velocity vector V i With instantaneous velocity vector V i-1 The difference is compared with the set speed threshold range, when the instantaneous velocity vector V i With instantaneous velocity vector V i-1 When the difference exceeds the velocity threshold, the i-th trajectory point is considered an anomaly and is removed; when the instantaneous velocity vector V i With instantaneous velocity vector V i-1 If the difference does not exceed the speed threshold range, then the i-th trajectory point is not an anomaly.

[0072] The Alpha-Shape algorithm is used to extract the convex hull of the filtered RTK positioning card's trajectory point set to generate a stacked boundary. First, Delaunay triangulation or tetrahedral subdivision is constructed to obtain all simplexes. The circumsphere radius r of each simplex is calculated. Then, the Alpha parameter α is set, and simplexes that satisfy r < α are retained. The outer surface of all retained simplexes is the Alpha-Shape. When α → ∞, it degenerates into a convex hull. The convex hull at this time is the outermost contour of the stacked shape. The Alpha-Shape can be regarded as the generalized convex hull of the point set.

[0073] Based on the stack boundary, non-uniform rational B-spline NURBS is used for surface fitting to construct a continuous surface, resulting in a three-dimensional cargo stack model. First, control points are extracted; the vertex set of the Alpha-Shape is directly used as the control points Pi,j of the NURBS surface. Then, node vectors are defined, and non-uniform node vectors are constructed in the u and v directions respectively. , The repetition at both ends is equal to the surface order p and q, where p is the order in the u direction and q is the order in the v direction. Then, weights are assigned, with each control point given a weight ωi,j>0. Weights ωi,j are usually set to 1; if local features need to be emphasized, the weights of corresponding points can be appropriately increased. The calculation process for constructing the continuous surface is shown below:

[0074]

[0075] In the formula, N i,p Let ω be a rational B-spline NURBS basis function. i,j As the weight, P i,j denoted as control points of the 3D cargo stack model; m and n represent the total number of control point grids in the u and v directions, respectively; i represents the basis function and control point in the i-th row or i-th direction in the u direction, and j represents the basis function and control point in the j-th row or j-th direction in the v direction.

[0076] In the step S4, the temperature and the spatial positioning of the temperature measuring point are fused with the three-dimensional cargo stack model to update the real-time cargo stack temperature gradient thermal map; the position of the temperature measuring point in the three-dimensional cargo stack model is calculated through the GPS coordinates and the offset of the temperature measuring point, so that the spatial positioning is fused, wherein the GPS coordinates of the temperature measuring point are the spatial positioning; the actual position of the temperature measuring point in the three-dimensional cargo stack model coordinate system is calculated, so that the spatial positioning of each temperature measuring point is corresponded to the specific position of the temperature measuring point in the three-dimensional cargo stack model, and the calculation process is as follows:

[0077]

[0078] In the formula, Ptemp is the actual position of the temperature measuring point in the three-dimensional cargo stack model coordinate system, P GPS is the GPS coordinates recorded by the temperature measuring point, is the on-site coordinate offset, which is the difference between the reference point positioned by the RTK positioning card and the reference point positioned by the GPS coordinates.

[0079] The temperature interpolation algorithm and the inverse distance weighting method are adopted, and the continuous temperature field is generated based on the adjacent temperature measuring points weighted, so that the real-time cargo stack temperature gradient thermal map is obtained; the grid vertex is (x, y), n temperature measuring points are known, the distance d i of the grid point to the temperature measuring point is calculated, the grid point is the grid vertex, and the calculation process is as follows:

[0080]

[0081] According to the distance d i of the grid point to the temperature measuring point, the weight w i =1 / d k i is obtained, wherein k is an attenuation factor, k>0, and k is usually taken as 2; the interpolation temperature T(x, y) is calculated, and the calculation process is as follows:

[0082]

[0083] In the formula, k is an attenuation factor, and d i is the distance of the grid point to the temperature measuring point.

[0084] For each grid vertex (x, y), the temperature difference approximate gradient of the adjacent vertex is adopted to generate a continuous temperature field through gradient calculation, so that the real-time cargo stack temperature gradient thermal map is obtained; the calculation formula is as follows:

[0085]

[0086] In the formula, , , is the grid unit size, e x , ey , e z The unit vectors corresponding to the x direction, y direction and z direction respectively, and finally, thermal rendering is performed, temperature values are mapped to colors, and gradient directions are superimposed on the color chart in the form of vector arrows or flow lines to intuitively show the heat flow direction.

[0087] In the step S5, the temperature of each region in the temperature gradient thermal map of the cargo pile is compared with the corresponding temperature threshold value to determine whether the temperature of the cargo pile reaches the high-temperature early warning, and if so, the mobile terminal alarm is triggered. The temperature of the core region in the temperature gradient thermal map of the cargo pile is compared with the core region temperature threshold value, and when the temperature of the core region is greater than or equal to the core region temperature threshold value, it is determined that the temperature of the cargo pile reaches the high-temperature early warning, the mobile terminal alarm is triggered, and the staff is notified to handle, for example, to ventilate, water or turn over the cargo pile to reduce the temperature of the cargo pile. When the temperature of the core region is less than the core region temperature threshold value, it is determined that the temperature of the cargo pile does not reach the high-temperature early warning, and the mobile terminal alarm is not triggered. The temperatures of other regions in the temperature gradient thermal map of the cargo pile can also be compared with the corresponding temperature threshold values, and when they are greater than the set temperature threshold values, early warning can be performed. Or when the temperature of any region in the temperature gradient thermal map of the cargo pile exceeds the set temperature threshold value, the mobile terminal alarm is triggered, and the staff is notified to handle the temperature dissipation.

[0088] At the same time, the steep slope of the cargo pile is determined by the three-dimensional cargo pile model to determine whether the steep slope of the cargo pile reaches the early warning requirement. The slope of the cargo pile is determined to determine whether the slope of the cargo pile reaches the early warning requirement, and when the slope of the cargo pile is greater than or equal to the set slope threshold value, the early warning requirement is reached, the mobile terminal alarm is triggered, and the staff is notified to handle and eliminate the danger. When the slope of the cargo pile is less than the set slope threshold value, the early warning requirement is not reached, and the mobile terminal alarm is not triggered.

[0089] The above is only a description of the preferred embodiments of the present application, and those skilled in the art can make some modifications and optimizations based on the above disclosure without departing from the above basic principles. These improvements and optimizations should be considered as the scope of protection of the present application.

Claims

1. A method for real-time updating of cargo pile data based on dynamic mapping and temperature inspection, characterized in that: The method comprises the following steps: S1, using RTK positioning technology to record the trajectory around the edge of the cargo pile, and generating a real-time pile shape trajectory map of the cargo pile; S2, using a temperature measuring rod to measure the temperature in different directions and at different depths of the cargo pile, and recording the temperature and spatial positioning of the temperature measuring points; S3, fitting the real-time pile shape trajectory map of the cargo pile based on the pile shape reconstruction module in the data fusion engine to obtain a three-dimensional cargo pile model; S4, based on the temperature field mapping module in the data fusion engine, fusing the temperature and spatial positioning of the temperature measuring points with the three-dimensional cargo pile model to update a real-time cargo pile temperature gradient thermal map; S5, comparing the temperature of each region in the cargo pile temperature gradient thermal map with the corresponding temperature threshold value to determine whether the temperature of the cargo pile reaches the high temperature early warning, and if so, triggering the mobile terminal alarm.

2. The method of claim 1, wherein: In the step S1, the RTK positioning technology realizes centimeter-level positioning through the cooperation of the reference station and the flow station to generate the edge trajectory of the cargo pile; the reference station and the flow station synchronously observe satellite signals, the reference station calculates the error between the carrier phase observation value and the theoretical value according to the observed satellite signals, and generates difference correction data; the flow station eliminates common errors by a double-difference observation model according to the received satellite signals and the difference correction data to obtain the trajectory points of the RTK positioning card, realizes the accurate positioning of the RTK positioning card, and obtains the trajectory point set of the RTK positioning card as the real-time pile shape trajectory map of the cargo pile, as shown below: In the formula, Pn is a track point of the nth RTK positioning card, x n , y n , and z n are three-dimensional coordinate points of the track point of the nth RTK positioning card on three-dimensional coordinate axes, respectively.

3. The method of claim 1, wherein: In the step S2, the temperature measuring rod is used to measure the temperature in different directions and at different depths of the cargo pile, and the spatial positioning of the temperature measuring points is recorded; the method comprises the following steps: S1-1, obtaining the number of bare surfaces of the cargo pile and the size of the cargo pile based on the real-time pile shape trajectory map of the cargo pile; S1-2, setting the number of temperature measuring points, the temperature measuring depth and the temperature measuring times of each temperature measuring point of each bare surface of the cargo pile according to the size and the number of bare surfaces of the cargo pile; S1-3, setting the specific temperature measuring position of each bare surface according to the number and the temperature measuring depth of the temperature measuring points of each bare surface; S1-4, inserting the temperature measuring rod into the cargo pile for multiple temperature measurements according to the temperature measuring depth of each bare surface and the specific temperature measuring position of each bare surface, and recording the temperature and spatial positioning of the temperature measuring points.

4. The method of claim 3, wherein: The number C of the temperature measuring points of each bare surface is calculated according to the size of the cargo pile and the number of bare surfaces of the cargo pile, and the calculation process is as follows: In the formula, C is the number of temperature measuring points of each bare surface, M G is the number of bare surfaces of the cargo pile, M D is the size level coefficient of the cargo pile, the size level of the cargo pile is divided into small, medium, large and super large; α and β are the weight coefficients of the number of bare surfaces of the cargo pile and the size of the cargo pile respectively; ε is a compensation coefficient; round is an integral operation.

5. The method of claim 4, wherein: The temperature measuring depth of each bare surface is divided into shallow layer temperature measurement and deep layer temperature measurement, and the selection of the temperature measuring depth of each bare surface is set according to the size grade of the cargo pile; when the size grade of the cargo pile is small, the temperature measuring depth of each bare surface is shallow layer temperature measurement; when the size grade of the cargo pile is medium, the temperature measuring depth of each bare surface at least contains deep layer temperature measurement of one temperature measuring point, and the rest temperature measuring points are shallow layer temperature measurement; when the size grade of the cargo pile is large, the temperature measuring depth of each bare surface at least contains deep layer temperature measurement of two temperature measuring points, and the rest temperature measuring points are shallow layer temperature measurement; when the size grade of the cargo pile is super large, the temperature measuring depth of each bare surface at least contains deep layer temperature measurement of three temperature measuring points, and the rest temperature measuring points are shallow layer temperature measurement.

6. The method of claim 5, wherein: In the step S1-3, specific temperature measuring positions of each bare surface are set according to the number of temperature measuring points and the temperature measuring depth of each bare surface; when each bare surface does not contain temperature measuring points for deep layer temperature measurement, the temperature measuring positions of each bare surface are uniformly distributed around the center point of the bare surface, and the distance between each temperature measuring position and the center point of the bare surface is determined according to the number of temperature measuring points; the number of temperature measuring points of each bare surface is divided into four intervals; when the number of temperature measuring points of each bare surface is in the first interval, the distance between each temperature measuring position and the center point of the bare surface is S A ; when the number of temperature measuring points of each bare surface is in the second interval, the distance between each temperature measuring position and the center point of the bare surface is S B ; when the number of temperature measuring points of each bare surface is in the third interval, the distance between each temperature measuring position and the center point of the bare surface is S C ; when the number of temperature measuring points of each bare surface is in the fourth interval, the distance between each temperature measuring position and the center point of the bare surface is S D ; and the number of temperature measuring points in the first interval to the fourth interval increases in turn, .

7. The method of claim 5, wherein: When each bare surface contains deep temperature measurement temperature measurement points, each bare surface is divided into a central region and a peripheral region; the central region is a circular region with the center point of each bare surface as the center, and occupies 1 / 3 of the area of each bare surface; the area of each bare surface except the central region is the peripheral region; the deep temperature measurement temperature measurement positions are all set in the central region, and the deep temperature measurement temperature measurement positions are uniformly distributed in the central region; the shallow temperature measurement temperature measurement positions are all set in the peripheral region, and the shallow temperature measurement temperature measurement positions are uniformly distributed around the central region, and the distance from each shallow temperature measurement temperature measurement position to the edge of the central region is S T .

8. The method for real-time updating of the data of the cargo pile based on dynamic mapping and temperature inspection according to claim 1, characterized in that: In the step S3, the stack type heavy module fits the real-time cargo stack trajectory map into a three-dimensional cargo stack model. Firstly, the trajectory point set of the RTK positioning card is filtered by point cloud filtering to remove drift points. The trajectory point set of the filtered RTK positioning card is extracted by a convex hull based on an Alpha-Shape algorithm to generate a stack boundary. A continuous curved surface is constructed by surface fitting based on the stack boundary using a non-uniform rational B-spline (NURBS) to obtain a three-dimensional cargo stack model. In the formula, N i,p is a rational B-spline NURBS base function, ω i,j is a weight, P i,j is a control point of the three-dimensional cargo pile model.

9. The method for real-time updating of the data of the cargo pile based on dynamic mapping and temperature inspection according to claim 1, characterized in that: In the step S4, the temperature and spatial positioning of the temperature measuring point are fused with the three-dimensional cargo stack model to update a real-time cargo stack temperature gradient thermal map. The position of the temperature measuring point in the three-dimensional cargo stack model is calculated through GPS coordinates and offset to realize the fusion of spatial positioning, and the calculation process is as follows: In the formula, Ptemp is the actual position of the temperature measurement point in the three-dimensional cargo stack model coordinate system, P GPS GPS coordinates recorded for the temperature measurement point, is the on-site coordinate offset; A temperature interpolation algorithm and an inverse distance weighting method are used, and a continuous temperature field is generated based on the weighted adjacent temperature measuring points to further obtain a real-time cargo stack temperature gradient thermal map. Let the grid vertex be (x, y), and n temperature measuring points be known. The interpolation temperature T(x, y) is calculated, and the calculation process is as follows: where k is an attenuation factor, d i is the distance from the grid point to the temperature measurement point; For each grid vertex (x, y), the temperature difference approximate gradient of the adjacent vertex is used to generate a continuous temperature field through gradient calculation to further obtain a real-time cargo stack temperature gradient thermal map. The calculation formula is as follows: For each grid vertex (x, y), the temperature difference approximate gradient of the adjacent vertex is used to generate a continuous temperature field through gradient calculation to further obtain a real-time cargo stack temperature gradient thermal map. The calculation formula is as follows: wherein , , is the grid cell size.

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