CN117782005A - Equipment settlement deformation monitoring method and system - Google Patents
Equipment settlement deformation monitoring method and system Download PDFInfo
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Abstract
The invention belongs to the technical field of intelligent perception, and particularly relates to a method and a system for monitoring sedimentation deformation of equipment. According to the obtained laser point cloud data corresponding to the tested equipment, curvature data and elevation data of each monitoring point of the tested equipment are obtained; judging the sedimentation deformation condition of the tested equipment according to the curvature data and the elevation data of each monitoring point, and monitoring the sedimentation deformation of the equipment; the method is equivalent to taking curvature data and elevation data of each monitoring point as parameters for monitoring sedimentation deformation, not only considers the sedimentation condition of the device in the vertical direction through the elevation data of the surface of the tested device, but also considers the deformation condition of the surface of the device caused by sedimentation and other reasons through the curvature data of the surface of the tested device, so that the sedimentation deformation condition can be monitored more comprehensively, the accuracy of sedimentation monitoring results is improved, and timely and reliable discovery of sedimentation deformation faults through the sedimentation deformation monitoring is ensured.
Description
Technical Field
The invention belongs to the technical field of intelligent perception, and particularly relates to a method and a system for monitoring sedimentation deformation of equipment.
Background
The sedimentation deformation to a large extent can negatively influence the operation condition of corresponding equipment, and even cause equipment failure; the settlement deformation condition of the corresponding equipment is one of effective measures for ensuring the safe and reliable operation of the equipment, and the current monitoring scheme used at home and abroad comprises the following steps: a laser image sedimentation monitoring system, a measuring robot system and the like. The laser image settlement monitoring system has the advantages of small volume, high response speed, good long-term stability and long-distance bus transmission. But the price is higher, and the data jump is easily caused by the influence of environmental conditions outdoors; the measuring robot has long measuring distance and high horizontal measuring precision. But the price is high, the measurement precision in the vertical direction is not ideal, and the requirement on the installation environment is extremely high; for monitoring the deformation of a corrugated pipe in GIS equipment, the method mainly uses point type scale measurement in the past, has low monitoring efficiency and low precision, and cannot realize real-time monitoring; the current development of electrical measurement mode has the problem that the zero drift of the resistance strain gauge for strain measurement causes serious distortion of long-term test results.
The Chinese patent application publication No. CN112880639A presents a method for monitoring the subsidence of the ground in a mining subsidence area based on three-dimensional laser scanning; acquiring point cloud data at each measuring station by a three-dimensional laser scanner, acquiring complete earth surface point cloud data through data splicing and coordinate conversion, and generating a digital elevation model according to the complete earth surface point cloud data so as to acquire elevation data of each point of the earth surface; repeating the operation in the next observation period to obtain elevation data of each point of the earth surface, and subtracting the elevation data of the two times to obtain sedimentation deformation of each point of the earth surface in the two adjacent observation periods; however, the elevation data can only indicate the deformation condition in elevation, such as the subsidence deformation condition of the surface plane, and for most of devices with various shapes and structures, the subsidence deformation condition and the presentation form are complex, so that the method cannot fully monitor the subsidence deformation condition, and the subsidence monitoring result is inaccurate, so that the faults are difficult to be timely and reliably found through the subsidence deformation monitoring.
Disclosure of Invention
The invention aims to provide a device settlement deformation monitoring method and system, which are used for solving the problems that the conventional settlement deformation monitoring method cannot comprehensively monitor settlement deformation conditions, so that the settlement monitoring result is inaccurate, and faults are difficult to be timely and reliably found through settlement deformation monitoring.
In order to achieve the above purpose, the invention provides a device sedimentation deformation monitoring method, which obtains curvature data and elevation data of each monitoring point of a device according to acquired laser point cloud data corresponding to tested devices; and judging the sedimentation deformation condition of the equipment according to the curvature data and the elevation data of each monitoring point.
Further, according to curvature data and elevation data of each monitoring point, a manner of judging sedimentation deformation conditions of the equipment comprises:
respectively obtaining a shape index value and an elevation value of each monitoring point according to the curvature data and the elevation data, and obtaining an elevation difference of each monitoring point according to the elevation value and a standard elevation value of each monitoring point; and judging the sedimentation deformation condition of the equipment according to the shape index value and the elevation difference.
Further, the method for judging the sedimentation deformation condition of the equipment according to the shape index value and the elevation difference comprises the following steps: comparing the shape index value and the elevation difference of each monitoring point obtained currently with the shape index value and the elevation difference of each monitoring point in the equipment shape and position historical fingerprint library, and judging the settlement deformation condition of the equipment according to the comparison result;
or, leading the shape index value and the elevation difference of each monitoring point which are obtained currently into a settlement deformation judgment model of the equipment, and determining the settlement deformation condition of the equipment according to the judgment result output by the settlement deformation judgment model; and the settlement deformation judgment model is obtained through training according to the equipment shape and position historical fingerprint library.
Further, the curvature data includes a principal curvature at each monitoring point; the laser point cloud data corresponding to the tested equipment comprises first point cloud data; the first point cloud data is obtained by carrying out data processing on the collected initial point cloud data of the tested equipment; the method for obtaining the curvature data of each monitoring point of the device according to the laser point cloud data corresponding to the tested device comprises the following steps:
respectively determining k neighborhood of points corresponding to each monitoring point in the first point cloud data, establishing local base surface and surface fitting according to the points corresponding to each monitoring point and the points in the k neighborhood of each monitoring point, solving the corresponding curved surface at each monitoring point, and determining the main curvature at each monitoring point;
the k neighborhood of the point corresponding to the monitoring point refers to a data set containing data of k points closest to the point corresponding to the monitoring point in the first point cloud data.
Further, the method for obtaining the elevation data of each monitoring point of the device comprises the following steps: obtaining a digital elevation model of the equipment according to the (x, y, z) coordinates of the points corresponding to each monitoring point in the first point cloud data; and obtaining elevation data of each point on the surface of the tested equipment according to the digital elevation model.
Further, the establishing mode of the device shape and position history fingerprint library comprises the following steps: and taking the elevation data and the shape index value of the initial surface monitoring point of the tested equipment before the equipment settlement deformation monitoring is started and the evaluation result of whether the equipment is settled deformation or not as initial data of an equipment shape position historical fingerprint library, and then continuously supplementing the data in the equipment shape position historical fingerprint library according to the elevation data and the shape index value of the monitoring point obtained by monitoring and the judged settlement deformation condition of the tested equipment in the equipment settlement deformation monitoring process.
Further, the acquisition mode of the initial point cloud data of the tested equipment comprises the following steps:
carrying out laser scanning on the tested equipment through different scanning units, and acquiring initial point cloud data of the tested equipment; setting corresponding targets for each scanning unit, wherein the overlapping area of the adjacent scanning units during laser scanning comprises a set number of targets or more;
the data processing mode comprises the following steps: and carrying out coordinate conversion on the initial point cloud data according to targets of overlapping areas when adjacent scanning units carry out laser scanning so as to unify the initial point cloud data under coordinate systems corresponding to different scanning units into the same coordinate system.
Further, the device under test comprises a bus and a GIL device.
The equipment settlement deformation monitoring method has the beneficial effects that: the curvature data and the elevation data of each monitoring point are used as parameters for monitoring sedimentation deformation, the sedimentation condition of the vertical direction of the device is considered through the elevation data of the surface of the device to be tested, and the deformation condition of the surface of the device caused by sedimentation and other reasons is considered through the curvature data of the surface of the device to be tested, so that the sedimentation deformation condition can be monitored more comprehensively, the accuracy of sedimentation monitoring results is improved, and timely and reliably finding out sedimentation deformation faults through the sedimentation deformation monitoring is ensured.
The invention also provides a device sedimentation deformation monitoring system, which comprises a processor, wherein executable program instructions are stored in the processor, and the executable program instructions are used for being executed to realize the device sedimentation deformation monitoring method.
The equipment settlement deformation monitoring system can achieve the same beneficial effects as the equipment settlement deformation monitoring method.
Drawings
FIG. 1 is a block flow diagram of a method for monitoring the sedimentation deformation of equipment in an embodiment of the method for monitoring the sedimentation deformation of equipment of the invention;
FIG. 2 is a schematic diagram of the principle of projection of points in the p and k neighbors to a tangential plane in an embodiment of the method for monitoring sedimentation deformation of equipment of the present invention;
FIG. 3 is a schematic diagram of parameterizing coordinate values of projection points in an embodiment of a method for monitoring sedimentation deformation of an apparatus according to the present invention;
FIG. 4 is a flow chart of a method for establishing a settlement deformation judgment model in an embodiment of the settlement deformation monitoring method of the invention.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent.
Method embodiment for monitoring sedimentation deformation of equipment
The embodiment provides a technical scheme of a device settlement deformation monitoring method, and referring to fig. 1, the monitoring method obtains curvature data and elevation data of each monitoring point of tested equipment according to acquired laser point cloud data corresponding to the tested equipment; and judging the sedimentation deformation condition of the equipment according to the curvature data and the elevation data of each monitoring point.
According to the monitoring method, curvature data and elevation data of each monitoring point are used as parameters for monitoring sedimentation deformation, the sedimentation condition of the device in the vertical direction is considered through the elevation data of the surface of the tested device, and the deformation condition of the surface of the device caused by sedimentation and other reasons is considered through the curvature data of the surface of the tested device, so that the sedimentation deformation condition can be monitored more comprehensively, the accuracy of a sedimentation monitoring result is improved, and timely and reliable detection of sedimentation deformation faults through the sedimentation deformation monitoring is ensured.
In this embodiment, the manner of determining the sedimentation deformation condition of the tested device according to the curvature data and the elevation data of each monitoring point includes:
the method comprises the steps of obtaining a shape index value and an elevation value of each monitoring point according to curvature data and elevation data of each monitoring point, and obtaining an elevation difference of each monitoring point according to the obtained elevation value and a standard elevation value of each monitoring point; and judging the sedimentation deformation condition of the tested equipment according to the shape index value and the elevation difference of each monitoring point.
Since in the actual process, the maximum, minimum, average curvature and gaussian curvature determined by the principal curvature have no unified standard, and cannot be effectively compared, a concept that has both unified standard and can display curvature characteristics of the object surface needs to be sought; the shape index value is selected as a parameter for representing the surface shape of the tested equipment, so that the situation of the surface sedimentation deformation of the tested equipment can be conveniently determined by comparison; the concept of shape index values is proposed by Koenderink and dorn, which is a combination of mean and gaussian curvatures; according to the shape index value, the concave-convex of the shape on the curved surface can be divided into a section of 0 to 1; specifically, the curvature data includes a principal curvature at each monitoring point, facilitating calculation of a shape index value.
The laser point cloud data corresponding to the tested equipment comprises first point cloud data, and the first point cloud data is obtained by carrying out data processing on the collected initial point cloud data of the tested equipment; the method for obtaining curvature data of each monitoring point of the tested equipment according to the laser point cloud data corresponding to the tested equipment comprises the following steps:
respectively determining k neighborhood of points corresponding to each monitoring point in the first point cloud data, establishing local base surface and surface fitting according to the points corresponding to each monitoring point and the points in the k neighborhood of each monitoring point, solving the corresponding curved surface at each monitoring point, and determining the main curvature at each monitoring point; the k neighborhood of the point corresponding to the monitoring point refers to a data set containing data of k points closest to the point corresponding to the monitoring point in the first point cloud data; specifically, the euclidean distance between a point in the first point cloud data corresponding to a certain monitoring point (i.e. the point corresponding to the monitoring point) and all other points in the first point cloud data is calculated, and then the k points arranged at the forefront are k nearest neighboring points contained in the k neighborhood, namely k nearest points.
Wherein the process of establishing the local base surface comprises the following steps: parameterizing a local base plane, namely taking a point p corresponding to a monitoring point from the first point cloud data, wherein the point in the k adjacent area of the point p is represented as Nb (p) = { p1, …, pk }; let the micro-tangential plane at point P be denoted as T (P) and take it as a local base, then find the projected points of the points in the neighborhood of point P and k on tangential plane T (P), to distinguish the projected points, mark the corresponding projected points as P ' and Nb (P ') = { P ' 1 ,...,p' n -referring specifically to fig. 2;
on the tangential plane, the projection point p 'farthest from the projection point p' of the point p is found by the projection point set Nb (p ')' i Junction p 'and p' i And orient the directionThe u-axis is defined, and a straight line perpendicular to the u-axis is defined as the v-axis. As shown in FIG. 3, when two direction axes are determined, each projection point is connected with a point p' to obtain n directional line segments, the line segments with directions are respectively subjected to dot products with the u axis and the v axis, for example, the dot product value with the u direction is recorded as d j Sorting all the obtained values to obtain maximum and minimum values, wherein the minimum value is marked as d min The maximum value is denoted as d max The method comprises the steps of carrying out a first treatment on the surface of the Parameterization is then performed by the following equation:
from the above equation, the parameterization of the coordinate value of the point set Nb (p') can be obtained, and the parameterization of the coordinate value of the v axis can be obtained by using a similar method, so that the local base surface value of the point parameterization corresponding to the monitoring point is obtained.
The process of the quadratic parameter surface fitting (i.e. surface fitting) of the local surface comprises the following steps: on the basis of new direction coordinate axes u and v obtained by parameterization of the above local base surface, adding a vertical direction axis n to form a space three-dimensional coordinate system, namely a Cartesian coordinate system, and then performing surface fitting in the new coordinate system by a least square method, wherein the following formula is shown:
S(u,v)＝(u,v,au 2 +buv+cv 2 )
converting a fitting formula of a curved surface into a form ax=b represented by a matrix, wherein
After the parameters a, b and c in the formula are obtained, the principal curvature k of the curved surface corresponding to the monitoring point 1 ，k 2 The expression can be obtained by the following expression.
The concept of shape index values is proposed by Koenderink and Doorn, is derived from the concept of average curvature and Gaussian curvature, and can be specifically calculated directly according to the principal curvature, and the calculation formula is shown as follows:
after the calculation of the formula of the shape index value, the concave-convex of the shape on the curved surface corresponding to the monitoring point can be divided into the interval of 0 to 1 through the shape index value.
The method for obtaining the elevation data of each monitoring point of the tested equipment comprises the following steps:
obtaining a digital elevation model of the equipment according to the (x, y, z) coordinates of the points corresponding to each monitoring point in the first point cloud data; and obtaining elevation data of each point on the surface of the tested equipment according to the digital elevation model. In this embodiment, the obtained elevation data of each monitoring point of the tested device is directly an elevation value, which is respectively I 1 、I 2 、I 3 、…I n Wherein n is the number of the monitoring points, and the obtained elevation value and the standard elevation value I of each monitoring point are used 01 、I 02 、I 03 、…I 0n The elevation difference of each monitoring point is obtained to be V 1 ＝I 1 -I 01 、V 2 ＝I 2 -I 02 、V 3 ＝I 3 -I 03 、…V n ＝I n -I 0n 。
For the first point cloud data, the acquisition mode of the initial point cloud data of the tested device comprises the following steps: carrying out laser scanning on the tested equipment through different scanning units, and acquiring initial point cloud data of the tested equipment; setting corresponding targets for each scanning unit, wherein the overlapping area of the adjacent scanning units when performing laser scanning comprises a set number of targets and more, in the embodiment, the set number is 3 in consideration of the compatibility requirement of calculation efficiency and calculation accuracy, namely, the overlapping area of the adjacent 2 scanning units is provided with 3 or more targets; the setting is convenient for unify the point cloud data under different coordinate systems to the same coordinate system by taking the targets of the overlapping areas as references, and the initial point cloud data acquired by different subsequent scanning units can be spliced to acquire the whole initial point cloud data, so that the splicing precision is high.
The data processing of the collected initial point cloud data of the tested device to obtain the first point cloud data comprises the following steps: and according to targets of overlapping areas when adjacent scanning units perform laser scanning, performing coordinate conversion on the initial point cloud data of the tested equipment so as to unify the initial point cloud data under the coordinate systems corresponding to different scanning units into the same coordinate system. Specifically, the method for processing data comprises the steps of filtering, thinning, correcting, splicing, dividing and the like, and the step of removing noise in initial point cloud data by adopting the modes of median filtering, average filtering, standard Gaussian method and the like besides coordinate conversion, so as to finally obtain first point cloud data; since these processes performed on the initial point cloud data (i.e., the initial three-dimensional laser point cloud data) belong to the prior art, a detailed description thereof is omitted herein.
In addition, in this embodiment, the method for judging the sedimentation deformation condition of the tested device according to the shape index value and the elevation difference of each monitoring point specifically includes:
comparing the shape index value and the elevation difference of each monitoring point obtained currently with the shape index value and the elevation difference of each monitoring point in the equipment shape and position historical fingerprint library, and judging the sedimentation deformation condition of the equipment to be tested according to the comparison result; the main results are four: no sedimentation and no deformation, and sedimentation and no deformation. For example, if the differences between the shape index value and the elevation difference of each monitoring point obtained currently and the shape index value and the elevation difference of each monitoring point in the equipment shape and position historical fingerprint library are not greater than the corresponding set difference threshold values respectively, judging that sedimentation and deformation are not generated; if the difference between the shape index value of each monitoring point obtained currently and the shape index value of each monitoring point in the equipment shape position historical fingerprint library is larger than a corresponding set difference threshold value, judging that deformation exists; if the difference between the currently obtained elevation difference of each monitoring point and the elevation difference of each monitoring point in the equipment shape and position historical fingerprint library is larger than a corresponding set difference threshold value, determining that sedimentation exists; combining the judging results to obtain the four judging results.
Or, leading the shape index value and the elevation difference of each monitoring point obtained currently into a settlement deformation judgment model of the tested equipment, and determining the settlement deformation condition of the tested equipment according to the judgment result output by the settlement deformation judgment model; the settlement deformation judgment model is obtained through training according to the historical fingerprint library of the shape and the position of the equipment.
The method comprises the steps that the initial values of the shape index values and the elevation differences of all monitoring points in an equipment shape and position historical fingerprint library are the shape index values and the elevation differences of all the monitoring points corresponding to a three-dimensional structure model of the true size of the tested equipment according to coordinate data of point cloud data; the three-dimensional structure model can be constructed through a delivery drawing, or can be constructed by collecting point cloud data through a three-dimensional laser device before the settlement deformation monitoring of the device is started.
The settlement deformation judgment model is obtained through training according to the historical fingerprint library of the shape and the position of the equipment. The monitoring method judges the sedimentation deformation condition of the tested equipment corresponding to the shape index value and the elevation difference of each monitoring point through the equipment shape position historical fingerprint library storing the shape index value and the elevation difference historical data of each monitoring point, and the judgment condition or the judgment standard corresponding to the sedimentation deformation is obtained according to the shape index value and the elevation difference historical data, so that the judgment result can be more in line with the actual sedimentation condition.
Specifically, referring to fig. 4, in the training process of the settlement deformation judgment model, in this embodiment, the model is constructed and trained by adopting a neural network structure, and other specific modes basically belong to the prior art except for different input training sets, so that details are not repeated here.
In this embodiment, the device settlement deformation monitoring method is mainly applied to related devices of metal-enclosed gas-insulated switchgear (abbreviated as GIS device), and specifically, the device under test includes a bus and a GIL device. The equipment settlement deformation monitoring method basically does not need to change the monitoring process and principle of the equipment settlement deformation monitoring method when applied to different tested equipment, so that the monitoring mode can be adopted no matter the equipment settlement deformation monitoring method is suitable for GIS related equipment such as bus and GIL equipment and the like, or is suitable for other types of tested equipment.
Device settlement deformation monitoring System embodiment
The embodiment provides a technical scheme of a device sedimentation deformation monitoring system, which comprises a processor, wherein executable program instructions are stored in the processor and are used for being executed to realize the device sedimentation deformation monitoring method in the device sedimentation deformation monitoring method embodiment.
Since the specific working process and working principle of the device sedimentation deformation monitoring system in this embodiment have been described in detail in the above embodiment of the device sedimentation deformation monitoring method, the details are not repeated here.
The invention has the following characteristics:
1) The curvature data and the elevation data of each monitoring point are used as parameters for monitoring sedimentation deformation, the sedimentation condition of the vertical direction of the device is considered through the elevation data of the surface of the device to be tested, and the deformation condition of the surface of the device caused by sedimentation and other reasons is considered through the curvature data of the surface of the device to be tested, so that the sedimentation deformation condition can be monitored more comprehensively, the accuracy of sedimentation monitoring results is improved, and timely and reliably finding out sedimentation deformation faults through the sedimentation deformation monitoring is ensured.
2) The shape index value determined by the principal curvature is selected as a parameter for representing the surface shape of the tested equipment, so that the unified standard is available, the curvature characteristics of the object surface can be displayed, and the condition of the surface subsidence deformation of the tested equipment can be determined conveniently by comparison.
3) And judging the sedimentation deformation condition of the tested equipment corresponding to the currently obtained shape index value and the elevation difference of each monitoring point through an equipment shape position historical fingerprint library storing the historical data of the shape index value and the elevation difference of each monitoring point, wherein the judgment condition or the judgment standard corresponding to the sedimentation deformation is obtained according to the historical data of the shape index value and the elevation difference, and the judgment result can be more in accordance with the actual sedimentation condition.
It is to be understood that the above-described embodiments of the present invention are merely illustrative of or explanation of the principles of the present invention and are in no way limiting of the invention.
Claims (9)
1. The equipment settlement deformation monitoring method is characterized in that curvature data and elevation data of each monitoring point of the equipment are obtained according to the acquired laser point cloud data corresponding to the tested equipment; and judging the sedimentation deformation condition of the equipment according to the curvature data and the elevation data of each monitoring point.
2. The method for monitoring the sedimentation deformation of the equipment according to claim 1, wherein the method for judging the sedimentation deformation condition of the equipment according to the curvature data and the elevation data of each monitoring point comprises the following steps:
respectively obtaining a shape index value and an elevation value of each monitoring point according to the curvature data and the elevation data, and obtaining an elevation difference of each monitoring point according to the elevation value and a standard elevation value of each monitoring point; and judging the sedimentation deformation condition of the equipment according to the shape index value and the elevation difference.
3. The method for monitoring sedimentation deformation of equipment according to claim 2, wherein the method for judging the sedimentation deformation condition of the equipment according to the shape index value and the elevation difference comprises the following steps: comparing the shape index value and the elevation difference of each monitoring point obtained currently with the shape index value and the elevation difference of each monitoring point in the equipment shape and position historical fingerprint library, and judging the settlement deformation condition of the equipment according to the comparison result;
or, leading the shape index value and the elevation difference of each monitoring point which are obtained currently into a settlement deformation judgment model of the equipment, and determining the settlement deformation condition of the equipment according to the judgment result output by the settlement deformation judgment model; and the settlement deformation judgment model is obtained through training according to the equipment shape and position historical fingerprint library.
4. A method of monitoring sedimentation deformation of a device according to any one of claims 1 to 3, in which the curvature data comprises the principal curvature at each monitoring point; the laser point cloud data corresponding to the tested equipment comprises first point cloud data; the first point cloud data is obtained by carrying out data processing on the collected initial point cloud data of the tested equipment; the method for obtaining the curvature data of each monitoring point of the device according to the laser point cloud data corresponding to the tested device comprises the following steps:
respectively determining k neighborhood of points corresponding to each monitoring point in the first point cloud data, establishing local base surface and surface fitting according to the points corresponding to each monitoring point and the points in the k neighborhood of each monitoring point, solving the surface at each monitoring point, and determining the main curvature at each monitoring point;
the k neighborhood of the point corresponding to the monitoring point refers to a data set containing data of k points closest to the point corresponding to the monitoring point in the first point cloud data.
5. A method of monitoring sedimentation deformation of a device according to any one of claims 1 to 3, wherein the means for obtaining elevation data for each monitoring point of the device comprises: obtaining a digital elevation model of the equipment according to the (x, y, z) coordinates of the points corresponding to each monitoring point in the first point cloud data; and obtaining elevation data of each point on the surface of the tested equipment according to the digital elevation model.
6. The method for monitoring sedimentation deformation of equipment according to claim 3, wherein the establishing manner of the historical fingerprint library of the shape and the position of the equipment comprises the following steps: and taking the elevation data and the shape index value of the initial surface monitoring point of the tested equipment before the equipment settlement deformation monitoring is started and the evaluation result of whether the equipment is settled deformation or not as initial data of an equipment shape position historical fingerprint library, and then continuously supplementing the data in the equipment shape position historical fingerprint library according to the elevation data and the shape index value of the monitoring point obtained by monitoring and the judged settlement deformation condition of the tested equipment in the equipment settlement deformation monitoring process.
7. The method for monitoring sedimentation deformation of equipment according to claim 4, wherein the acquisition mode of initial point cloud data of the equipment to be tested comprises:
carrying out laser scanning on the tested equipment through different scanning units, and acquiring initial point cloud data of the tested equipment; setting corresponding targets for each scanning unit, wherein the overlapping area of the adjacent scanning units during laser scanning comprises a set number of targets or more;
the data processing mode comprises the following steps: and carrying out coordinate conversion on the initial point cloud data according to targets of overlapping areas when adjacent scanning units carry out laser scanning so as to unify the initial point cloud data under coordinate systems corresponding to different scanning units into the same coordinate system.
8. A method of monitoring sedimentation deformation of a device according to any one of claims 1-3, characterized in that the device under test comprises a busbar and GIL device.
9. A device sedimentation deformation monitoring system comprising a processor having stored therein executable program instructions for being executed to implement the device sedimentation deformation monitoring method of any one of claims 1-8.
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