CN111174721A - Hoisting mechanical structure deformation detection method based on three-dimensional laser scanning - Google Patents
Hoisting mechanical structure deformation detection method based on three-dimensional laser scanning Download PDFInfo
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- CN111174721A CN111174721A CN201911376879.9A CN201911376879A CN111174721A CN 111174721 A CN111174721 A CN 111174721A CN 201911376879 A CN201911376879 A CN 201911376879A CN 111174721 A CN111174721 A CN 111174721A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/16—Measuring arrangements characterised by the use of optical techniques for measuring the deformation in a solid, e.g. optical strain gauge
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/002—Measuring arrangements characterised by the use of optical techniques for measuring two or more coordinates
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Abstract
The invention belongs to the technical field of mechanical detection, particularly relates to a hoisting mechanical structure deformation detection method based on three-dimensional laser scanning, and aims to solve the problems that the existing method is high in measurement difficulty, the measurement result cannot reflect the deformation of the whole part, and the measurement result has large errors. The method comprises the steps that a tested hoisting machine and a corresponding target are scanned at each scanning station through a three-dimensional laser scanning device; splicing the obtained point cloud data to obtain characteristic information data of each point on the surface of the measured hoisting machinery under a unified coordinate system; reconstructing a three-dimensional model, and acquiring space coordinate data of each test point on a target plane of the three-dimensional model according to the test content; and calculating to obtain the structural deformation of the measured hoisting machinery. The invention can obtain the whole deformation of the mechanical part to be detected, and detection personnel do not need to carry out short-distance measurement, thereby improving the detection efficiency and reducing the measurement error caused by manual measurement.
Description
Technical Field
The invention belongs to the technical field of mechanical detection, and particularly relates to a hoisting mechanical structure deformation detection method based on three-dimensional laser scanning.
Background
Nowadays, the rapid development of national economy is that hoisting machinery is widely applied to industries such as metallurgy, electric power, ports, logistics, machine manufacturing, ocean engineering and the like. Many hoisting machines have the conditions of long service life, complex operation condition, variable load involved in the daily operation process, diversified shapes of the hoisted objects, irregular operation frequency and amplitude change, complex working environment, overload operation and the like. The existing problems easily cause the deformation of the whole or partial steel structure of the crane, thereby causing accidents such as direct fracture of the steel structure of the crane, collapse of the whole crane, tipping and the like.
The crane structure deformation detection is an important link in the crane inspection process and comprises crane main beam web local buckling deformation detection, crane no-load main beam upper camber detection, rated load main beam lower camber detection and the like.
The existing crane main beam web local buckling deformation detection method mainly comprises the steps of measuring a main beam internal web, measuring by using a measuring tool with the length of 1m and matching a steel ruler, and obtaining the maximum value of the gap between the inner side of the measuring tool and the web as a main beam web local buckling numerical value according to the measuring result.
The camber of the crane girder refers to the upward camber of the girder prefabricated and calculated by the horizontal line. The camber of the existing crane girder is mainly detected and measured by a level or a theodolite measuring method (a measuring point must be more than 2 meters away from a lens, a steel wire drawing (correcting) method and the like.
The lower deflection refers to the elastic deformation of the trolley in the main beam span and the main beam span downwards under the rated load, and is calculated from the actual position before loading. The existing deflection measurement mainly utilizes a theodolite and a laser range finder to carry out measurement.
The existing measuring method needs to measure the tested equipment in a close range, so the measuring difficulty is high, and the number of measuring personnel is large; the selection of the measurement position is local selection, the whole deformation of the measured mechanical part cannot be obtained, and the deformation condition of the whole part cannot be comprehensively reflected by the measurement result; the measurement error and the accumulated error of the measurement result are large.
Disclosure of Invention
Technical problem to be solved
The invention provides a hoisting mechanical structure deformation detection method based on three-dimensional laser scanning, and aims to solve the problems that an existing measurement method is high in measurement difficulty, the deformation condition of the whole part cannot be comprehensively reflected by a measurement result, and the measurement error and the accumulated error of the measurement result are large.
(II) technical scheme
In order to achieve the purpose, the invention adopts the main technical scheme that:
a hoisting mechanical structure deformation detection method based on three-dimensional laser scanning comprises the following steps:
s100, selecting a plurality of scanning stations according to the hoisting machinery to be tested and the field test environment, and laying targets according to the positions of the scanning stations;
s200, scanning the measured hoisting machinery and the corresponding target through a three-dimensional laser scanning device at each scanning station respectively to obtain first point cloud data;
step S300, performing data splicing on first point cloud data acquired by a plurality of scanning stations, and acquiring characteristic information data of each point on the surface of the measured hoisting machine under a unified coordinate system, wherein the characteristic information data comprises space coordinate data of each point on the surface of the measured hoisting machine;
s400, reconstructing a three-dimensional space model based on the characteristic information data to obtain a three-dimensional model of the measured hoisting machinery;
s500, selecting a plurality of test points from a target plane of the tested hoisting machinery three-dimensional model according to test indexes, and obtaining space coordinate data of each test point;
and S600, calculating the structural deformation of the measured hoisting machinery based on the space coordinate data.
As a modification of the present invention, after the step S200 is executed and before the step S300, the method further includes:
step S301, removing noise data in the first point cloud data acquired by each scanning station, wherein the noise data are point cloud data of other objects except the detected hoisting machinery and the target.
As a modification of the present invention, after the step S200 is executed and before the step S300, the method further includes:
and S302, optimizing the first point cloud data acquired by each scanning station, wherein the optimizing method comprises one or more of point cloud filtering, point cloud simplification, point cloud segmentation and point cloud classification.
As an improvement of the invention, the test indexes comprise: local deformation of girder web warping, camber deformation of girder and girder downwarp deformation.
As an improvement of the present invention, when the test index is a local deformation of a warp of a web of a main beam, the scanning station selection condition includes:
the included angle between the three-dimensional laser scanning device and the inner side webs of the two girders of the tested hoisting machinery is more than 30 degrees, and the included angle between the two sides of the girders and the vertical horizontal plane of the three-dimensional laser scanning device is more than 45 degrees.
As an improvement of the present invention, the target is a target ball, and the step S100 of arranging the targets according to the position of the scanning station includes:
the number of target balls in the same horizontal plane is 1 or 2;
the distance range between the target ball and the three-dimensional laser scanning device is 3 m-8 m;
the angle of the target ball between the three-dimensional laser scanning device and the ground is larger than 60 degrees.
As an improvement of the present invention, the configuration parameters of the three-dimensional laser scanning device include:
the point cloud parameter setting range is 8192 × 3413Pt to 10240 × 4267 Pt;
the angle of the horizontal area is 0-360 degrees, and the angle of the vertical area is-60-90 degrees;
closing the GPS positioning function;
the scanning distance is more than 10m indoors.
As an improvement of the present invention, the method for calculating the structural deformation amount includes:
ΔH＝H1-H2
wherein, Δ H is the structural deformation of the surface target point of the main beam web or the lower cover plate of the crane; h1The spatial Z-axis coordinate value of a target point on the surface of the crane girder in the same coordinate plane; h2And the space Z axis value of the target point on the surface of the main beam of the crane, which is vertical to the ideal plane point.
As an improvement of the present invention, when the test index is the deformation of the camber on the main beam, the calculation method of the structural deformation amount is as follows:
F＝D-D1
and F is the structural deformation obtained by measuring the upper camber, D is the highest point position coordinate of the midspan upper edge of the main beam, D1 is the highest point coordinate right above the end beam, and D is more than D1.
As an improvement of the present invention, when the test index is main beam downdeflection deformation detection, the calculation method of the structural deformation amount is as follows:
y＝∣L-L1∣
wherein y is a lower deflection value, L is the height of any point of the web of the girder before loading, and L1 is the height of any point of the web of the girder after loading.
(III) advantageous effects
The invention has the beneficial effects that: according to the invention, the three-dimensional laser scanner is used for comprehensively measuring the crane deformation, all spatial point information in the visible range of the crane can be uniformly acquired, and data required for calculating the deformation amount is more comprehensively acquired, so that the deformation information of the whole plane can be acquired, and the measurement error is reduced; the detection personnel do not need to measure in a short distance, so the detection efficiency is improved, the consumption of detection resources is saved, and the safety risk factor in the detection is reduced to the minimum; the whole deformation of the tested mechanical part can be obtained, and the measurement result provides reliable data support for the inspection result.
Drawings
The invention is described with the aid of the following figures:
fig. 1 is a schematic flow chart of a hoisting mechanical structure deformation detection method based on three-dimensional laser scanning according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a rectangular coordinate system of a three-dimensional laser scanning space according to an embodiment of the present invention;
FIG. 3 is a schematic view of a local warp deformation detection of a spar web in an embodiment of the present invention;
fig. 4 is a schematic flowchart of an embodiment of a method for detecting deformation of a hoisting mechanical structure based on three-dimensional laser scanning according to an embodiment of the present invention;
FIG. 5 is a field diagram of a test case in accordance with an embodiment of the present invention;
FIG. 6 is a schematic diagram of a target ball placement and standing position in accordance with an embodiment of the present invention;
FIG. 7a is a schematic diagram of the splicing of scanning stations of Scans software according to an embodiment of the present invention;
FIG. 7b is a schematic diagram illustrating identification of splice identification points in an embodiment of the present invention;
FIG. 7c is a schematic diagram illustrating the setting of the layout scan parameters for deriving the original model in the Scans software according to the embodiment of the present invention;
fig. 7d is a schematic diagram of setting parameters of derived scan points for deriving an original model in the Scans software according to the embodiment of the present invention;
fig. 8a is a schematic diagram of coordinates of a test point on a pickup plane according to an embodiment of the present invention;
FIG. 8b is a schematic diagram of spatial coordinates of points obtained by hiding a crane model according to an embodiment of the present invention;
FIG. 9a is a schematic diagram of a differential deformation curve according to an embodiment of the present invention;
FIG. 9b is a diagram illustrating the derivation of raw data according to an embodiment of the present invention.
Detailed Description
For the purpose of better explaining the present invention and to facilitate understanding, the present invention will be described in detail by way of specific embodiments with reference to the accompanying drawings.
The terms "first," "second," and the like are used for distinguishing between similar elements and not necessarily for describing or implying a particular order or sequence.
The invention refers three-dimensional laser scanning to crane detection industry, and provides a crane mechanical structure deformation detection method based on three-dimensional laser scanning, and fig. 1 is a flow schematic diagram of the crane mechanical structure deformation detection method based on three-dimensional laser scanning, and specifically comprises the following steps:
s100, selecting a plurality of scanning stations according to the hoisting machinery to be tested and the field test environment, and laying targets according to the positions of the scanning stations;
s200, scanning the tested hoisting machinery and the corresponding target through a three-dimensional laser scanning device at each scanning station respectively to obtain first point cloud data;
step S300, performing data splicing on first point cloud data acquired by a plurality of scanning stations, and acquiring characteristic information data of each point on the surface of the measured hoisting machinery under a unified coordinate system, wherein the characteristic information data comprises space coordinate data of each point on the surface of the measured hoisting machinery;
s400, reconstructing a three-dimensional space model based on the characteristic information data to obtain a three-dimensional model of the measured hoisting machinery;
s500, selecting a plurality of test points from a target plane of a tested hoisting machinery three-dimensional model according to test indexes, and obtaining space coordinate data of each test point;
and S600, calculating to obtain the structural deformation of the measured hoisting machinery based on the space coordinate data.
the three-dimensional laser scanning device can be a three-dimensional laser scanner, a laser transmitter is arranged in the three-dimensional laser scanner, the laser transmitter transmits laser beams according to a certain speed, the laser beams strike on a scanned object and are reflected back to be received by the instrument, the scanner calculates the time of laser emission and reflection so as to calculate the distance and the three-dimensional coordinates of the scanned object, the three-dimensional laser scanner not only measures the distance between the instrument and the object, but also obtains the relative position relation between the instrument and the target object through a shaft system in the instrument, so that unknown space position information of the object is obtained by using the known instrument coordinates.
X＝Scosθcosα (1)
Y＝Scosθsinα (2)
Z＝Ssinθ (3)
As a measuring device, the three-dimensional laser scanner has the following characteristics:
the method is a non-contact high-speed laser measurement means, does not need to use props such as a reflector and the like, directly obtains the three-dimensional coordinate data of the surface of a target object, and has no contact damage to the tested equipment;
the data acquisition process is full-automatic, the acquired data are digital signal data, the data reliability is high, the post analysis processing, the data output, the display and the like are easy, and the crane deformation detection efficiency is improved;
the three-dimensional laser scanning technology can rapidly acquire high-precision and high-density point cloud data, adopts a data acquisition mode of a dot matrix and a grid, has a full-automatic distance self-adaptive focusing function of a laser beam, is uniform in distribution of sampling points and high in resolution, and can intuitively reflect the integral deformation condition of a crane;
the three-dimensional laser scanner has extremely high scanning speed, and can obtain more than 100 ten thousand points of data coordinate information within a few seconds. The scanning measurement time of one station is as short as several minutes to tens of minutes;
when the three-dimensional laser scanner collects data, an external light source is not needed, the three-dimensional laser scanner independently emits signals, the measurement process is not limited by time and regions, all-weather measurement is realized, and the three-dimensional point cloud data information on the surface of the crane can be obtained in real time.
The invention is oriented to the inspection and calibration application of large-scale complex hoisting equipment, the data acquisition is carried out by scanning the whole structure of the crane without contact, the data is exported and processed, the key point information is obtained from the scanning point cloud data, and finally the deformation is obtained by calculation.
The invention provides a crane mechanical structure deformation detection method based on three-dimensional laser scanning, and the key technology comprises the steps of extending a three-dimensional scanning technology to crane deformation detection work, and making detailed introduction on test parameter setting of scanning equipment in a complex environment, avoidance of adverse factors of a test environment and special processing of a scanning result.
To facilitate an understanding of the present invention, a description of a prior art method of measuring local warpage of a web is provided below. FIG. 3 is a schematic view illustrating a detection of local buckling deformation of a spar web. The conventional detection method for the local deformation of the web plate of the main beam is flat ruler detection, the local deformation of the web plate of the main beam of the crane is mainly detected by using a 1m flat ruler in a traditional detection mode, and the maximum value of the gap between the inner side of a measuring tool and the web plate is the local warping value of the web plate of the main beam as a measurement result.
The embodiment provides a rapid scanning detection method for applying a three-dimensional imaging technology to deformation measurement of an integral structure of a main beam web of a hoisting machine, aiming at the problems that the existing measurement method is high in measurement difficulty, the measurement result cannot comprehensively reflect the deformation condition of the whole part, and the measurement error and the accumulated error of the measurement result are large. Fig. 4 is a schematic flow chart of an embodiment of a method for detecting deformation of a hoisting mechanical structure based on three-dimensional laser scanning according to an embodiment of the present invention, and the specific flow chart is shown in fig. 4.
S1, performing on-site survey of the crane working environment, testing and selecting a scanning position, and avoiding adverse factors of the scanning environment during selection;
s2, selecting a scanning area, and setting instrument parameters according to different test environments; the splicing surface between the scanning base stations is established and the target ball is placed, and noise points on a test site are cleaned and avoided according to the requirements of the method;
step S3, scanning the crane station by station;
and step S4, exporting data after data supplement, establishing a coordinate system, and denoising and filtering the point cloud. Data supplementation refers to that auxiliary splicing points which need to be added during model building need to be supplemented with data points or data surfaces (based on feature surface splicing) in a point cloud model when the number of splicing points is insufficient or splicing errors are large.
And step S5, splicing and noise point processing are carried out on the supplemented data. Because the original data model is composed of a plurality of point clouds, other redundant objects are inevitably collected together in the scanning process, and therefore the noise points need to be removed and cleaned.
S6, generating a crane three-dimensional model, and analyzing the whole girder web plate; the measurement point data is picked up to calculate a deformation value.
And step S7, obtaining the deformation condition of the crane according to the result obtained by analyzing and processing the main beam web.
The deformation condition of the crane girder is obtained by acquiring the point cloud information of the surface of the girder, and each point in the point cloud corresponds to the coordinate in the space system. The local deformation is overlapped by fitting an ideal plane and the measured hoisting mechanical model surface (such as a web plate or a lower cover plate of a main beam) obtained by scanning, wherein the difference is the absolute value of the deformation. The invention can overlap the whole web or lower cover plate (the complete plane obtained by any scanning) with an ideal plane to obtain the local deformation. For example, the following steps are carried out: the point coordinate can be obtained by picking up the coordinate of the point to be measured of the web plate of the girder to be measured, the whole coordinate plane is the same, the difference value between the point and the point, namely the relative coordinate value can be calculated through the coordinate of each point, and therefore the difference value between two points or multiple points can be calculated.
The measurement of the upper camber and the lower deflection of the main beam is calculated by the principle.
In order to make the objects, technical solutions and advantages of the present invention clearer, a method for detecting deformation of a hoisting mechanical structure based on three-dimensional laser scanning is applied to local warpage measurement of a web, and a specific example is as follows.
The project is to inspect and scan the girder steel structure of 700 tons of bridge crane underground in a certain hydropower station, and the operation range is set according to the actual position of the field hoisting equipment to eliminate blind areas. The scanning radius needs to be satisfied so that the scanning coverage of the three-dimensional laser scanner can be in the range of 0-180 degrees below the horizontal plane of the crane. The field test is shown in fig. 5.
Through the investigation of the field working environment, factors which can cause testing noise are eliminated: it is ensured that personnel not associated with the test work are not within the scanning range. Cleaning a spherical object on site with a shape similar to the target sphere: safety helmets, crews, and other interfering objects.
The scanning area is selected to enable the scanner and the inner flanks of two girders of the crane to be positionedplate included angle alpha1more than 30 degrees, and the included angle alpha between the two sides of the crossbeam and the vertical horizontal plane of the scanner2the number of target balls on the same horizontal plane is not more than 2, the optimal distance between the target balls and the three-dimensional laser scanner is 3-8 m, and the included angle alpha between the target ball placing device between the three-dimensional laser scanner and the ground and the scanner3> 60 deg. with 6 stations. If the number of the target balls in the single station is 3, the number of the target balls in the same plane in the space coordinate system cannot be 2. Fig. 6 is a schematic diagram showing the arrangement and standing positions of target balls, and the diagram is a top view of a main beam of the crane.
The scanning parameters are set on the premise of ensuring the completeness of scanning data, the point cloud number value in an effective measuring range is in the range of 8192 x 3413-10240 x 4267, and the point distance is controlled in the range of 7.7mm/10 m-6.1 mm/10 m. In order to ensure the optimal scanning quality and improve the scanning efficiency, the point cloud parameter setting is in the range of 8192 × 3413-10240 × 4267; closing the GPS positioning function; setting the horizontal area angle: 0 to 360 DEG, and a vertical region ranging from-60 to 90 DEG; adjusting the scanner to the horizontal according to the inclinometer; the scanning distance is adjusted to be more than 10m indoors. Scanning is started, and the scanning sequence has no influence on the scanning result.
And importing the scan data in the format of 'fls' acquired on site into Scans software for data processing. The six-station data are spliced on the basis of targets through 6 prefabricated target balls, the automatic clustering function is closed, and in order to ensure that the density of the point cloud is moderate, the point cloud sample is set to be three rows and three columns. The original data model in the "E57" source file format is derived. The point cloud processing steps are shown in fig. 7 a-7 d: FIG. 7a is a schematic diagram showing the splicing of scanning stations in the Scans software; FIG. 7b illustrates the identification of the spliced identification points (target balls), wherein the small yellow-green dots are the target balls; fig. 7c and 7d are parameter settings for deriving the original model in the Scans software.
The point cloud data is further optimized by cloudbcoarse software if necessary. The CloudCompare tool is an open source tool for processing point cloud data, and comprises a series of processing processes such as point cloud denoising, point cloud filtering, point cloud simplification, point cloud segmentation and classification, point cloud characteristic line extraction and the like.
And importing the generated source file in the E57 format into 3D point cloud data modeling software 3D DReshaper to perform splicing and noise point processing on the original model. Because the original data model is composed of several point clouds, other redundant objects are inevitably collected together during the scanning process, so that noise points beyond the expected result need to be eliminated and cleaned.
By picking up the coordinates of the test points on the plane, as shown in fig. 8 a; hiding the crane model, the spatial coordinates of each point can be obtained, as shown in fig. 8 b. The difference value between the point and the point, namely the relative coordinate value can be calculated through the coordinates of the points, so that the difference value between the two points or the multiple points can be calculated.
And (4) calculating the deformation amount of the local buckling structure of the main beam web according to the formula (4).
ΔH＝H1-H2(4)
Wherein, Δ H is the structural deformation of the surface target point of the main beam web or the lower cover plate of the crane; h1The spatial Z-axis coordinate value of a target point on the surface of the crane girder in the same coordinate plane; h2And the space Z axis value of the target point on the surface of the main beam of the crane, which is vertical to the ideal plane point. The ideal plane is based on the ideal plane fitted at the joint of the two ends of the main beam and the end beam.
And (4) calculating the camber deformation of the main beam according to the formula (5).
F＝D-D1(5)
Wherein D is the coordinate value of the highest point of the middle-span upper edge of the main beam, D1Is the coordinate value of the highest point right above the starting beam, wherein D is more than D1. Note that the difference must be "+", otherwise the calculation is invalid.
And (4) calculating the deflection of the deflection structure under the web plate of the main beam according to the formula (6).
y＝∣L-L1∣ (6)
Wherein y is the lower deflection value, L is the height of any point of the web of the girder before loading, L1And the height of any point of the web of the main beam after loading.
According to the requirements in TSG _ Q7015-2016, the allowable range of deflection of the crane at different working levels is shown in Table 1, wherein S is the span of the main beam.
TABLE 1
The "differential deformation" is selected under the local module to obtain the differential deformation curve, as shown in FIG. 9a, the horizontal axis represents the number of the selected target points (400 are selected). The vertical axis represents the offset of each target point based on the virtual horizontal plane. And after noise points are eliminated, selecting the maximum value of the variation deformation to compare and calculate the structural deformation. And (3) deriving original data, and selecting the space coordinates of the first 15 points in 400 points as shown in FIG. 9b, wherein the 'deviation' column in the data graph is a deviation numerical value, and the unit m is a measurement result of the local warping numerical value of the web of the girder.
It is conceivable that the method provided by the invention can also be used for detecting the perpendicularity of the support leg of the hoisting machine in the deformation detection of the hoisting machine structure.
The method utilizes a 'live-action replication technology' of three-dimensional laser scanning to quickly, accurately and efficiently capture three-dimensional point cloud data on the surface of the crane to acquire three-dimensional space information; and eliminating and weakening the influence of gross errors caused by the surface damage of the structure on the detection result by adopting a steady estimation method. The hoisting mechanical structure deformation detection method based on three-dimensional laser scanning can improve the detection efficiency, reduce the cost of detection personnel and provide more powerful and comprehensive data description for detection conclusions.
It should be understood that the above description of specific embodiments of the present invention is only for the purpose of illustrating the technical lines and features of the present invention, and is intended to enable those skilled in the art to understand the contents of the present invention and to implement the present invention, but the present invention is not limited to the above specific embodiments. It is intended that all such changes and modifications as fall within the scope of the appended claims be embraced therein.
Claims (10)
1. A hoisting mechanical structure deformation detection method based on three-dimensional laser scanning is characterized by comprising the following steps:
s100, selecting a plurality of scanning stations according to the hoisting machinery to be tested and the field test environment, and laying targets according to the positions of the scanning stations;
s200, scanning the measured hoisting machinery and the corresponding target through a three-dimensional laser scanning device at each scanning station respectively to obtain first point cloud data;
step S300, performing data splicing on first point cloud data acquired by a plurality of scanning stations, and acquiring characteristic information data of each point on the surface of the measured hoisting machine under a unified coordinate system, wherein the characteristic information data comprises space coordinate data of each point on the surface of the measured hoisting machine;
s400, reconstructing a three-dimensional space model based on the characteristic information data to obtain a three-dimensional model of the measured hoisting machinery;
s500, selecting a plurality of test points from a target plane of the tested hoisting machinery three-dimensional model according to test indexes, and obtaining space coordinate data of each test point;
and S600, calculating the structural deformation of the measured hoisting machinery based on the space coordinate data.
2. The method for detecting deformation of a hoisting mechanical structure based on three-dimensional laser scanning as claimed in claim 1, wherein after step S200 is executed and before step S300, the method further comprises:
step S301, removing noise data in the first point cloud data acquired by each scanning station, wherein the noise data are point cloud data of other objects except the detected hoisting machinery and the target.
3. The method for detecting deformation of a hoisting mechanical structure based on three-dimensional laser scanning as claimed in claim 1, wherein after step S200 is executed and before step S300, the method further comprises:
and S302, optimizing the first point cloud data acquired by each scanning station, wherein the optimizing method comprises one or more of point cloud filtering, point cloud simplification, point cloud segmentation and point cloud classification.
4. The hoisting mechanical structure deformation detection method based on three-dimensional laser scanning as claimed in claim 1, wherein the test index comprises: local deformation of girder web warping, camber deformation of girder and girder downwarp deformation.
5. The hoisting mechanical structure deformation detection method based on three-dimensional laser scanning as recited in claim 4, wherein when the test index is a local deformation amount of a warping of a web of a main beam, the scanning station selection conditions include:
the included angle between the three-dimensional laser scanning device and the inner side webs of the two girders of the tested hoisting machinery is more than 30 degrees, and the included angle between the two sides of the girders and the vertical horizontal plane of the three-dimensional laser scanning device is more than 45 degrees.
6. The method as claimed in claim 4, wherein the target is a target ball, and the step S100 of arranging the target according to the position of the scanning station includes:
the number of target balls in the same horizontal plane is 1 or 2;
the distance range between the target ball and the three-dimensional laser scanning device is 3 m-8 m;
the angle of the target ball between the three-dimensional laser scanning device and the ground is larger than 60 degrees.
7. The hoisting mechanical structure deformation detection method based on three-dimensional laser scanning as claimed in claim 4, wherein the configuration parameters of the three-dimensional laser scanning device comprise:
the point cloud parameter setting range is 8192 × 3413 to 10240 × 4267;
the angle of the horizontal area is 0-360 degrees, and the angle of the vertical area is-60-90 degrees;
closing the GPS positioning function;
the scanning distance is more than 10m indoors.
8. The hoisting mechanical structure deformation detection method based on three-dimensional laser scanning as claimed in any one of claims 5-7, wherein the calculation method of the structure deformation amount is as follows:
ΔH＝H1-H2
wherein, Δ H is the structural deformation of the surface target point of the main beam web or the lower cover plate of the crane; h1The spatial Z-axis coordinate value of a target point on the surface of the crane girder in the same coordinate plane; h2And the space Z axis value of the target point on the surface of the main beam of the crane, which is vertical to the ideal plane point.
9. The hoisting mechanical structure deformation detection method based on three-dimensional laser scanning as recited in claim 4, wherein when the test index is camber deformation on the main beam, the calculation method of the structural deformation amount is as follows:
F＝D-D1
wherein, F is the structural deformation obtained by the measurement of the upper camber, D is the position coordinate of the highest point of the span-middle upper edge of the main beam, and D is the position coordinate of the highest point of the span-middle upper edge of the main beam1The highest point coordinate right above the end beam is D > D1。
10. The hoisting machinery structure deformation detection method based on three-dimensional laser scanning of claim 4, wherein when the test index is main beam lower deflection deformation detection, the calculation method of the structure deformation amount is as follows:
y＝∣L-L1∣
wherein y is the lower deflection value, L is the height of any point of the web of the girder before loading, L1And the height of any point of the web of the main beam after loading.
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| CN112378476A (en) * | 2020-11-17 | 2021-02-19 | 哈尔滨工业大学 | Large length-diameter ratio horizontal tank volume multi-station three-dimensional laser scanning internal measurement device and method |
| CN112578327A (en) * | 2020-12-01 | 2021-03-30 | 深圳市通用测试系统有限公司 | Calibration method, equipment and storage medium of spherical scanning test system |
| CN113884049A (en) * | 2021-10-08 | 2022-01-04 | 包头钢铁（集团）有限责任公司 | Method for measuring horizontal bending of crane by using total station |
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| CN116839504A (en) * | 2023-07-28 | 2023-10-03 | 江苏省特种设备安全监督检验研究院 | Detection and early warning method and system for camber of crane |
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| CN112578327A (en) * | 2020-12-01 | 2021-03-30 | 深圳市通用测试系统有限公司 | Calibration method, equipment and storage medium of spherical scanning test system |
| CN112578327B (en) * | 2020-12-01 | 2023-09-12 | 深圳市通用测试系统有限公司 | Calibration method, device and storage medium of spherical scanning test system |
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| CN113884049A (en) * | 2021-10-08 | 2022-01-04 | 包头钢铁（集团）有限责任公司 | Method for measuring horizontal bending of crane by using total station |
| CN113916145A (en) * | 2021-10-15 | 2022-01-11 | 沈成鹏 | System and method for testing deflection of building steel structure |
| CN114088008A (en) * | 2021-10-18 | 2022-02-25 | 包头钢铁（集团）有限责任公司 | Method for measuring sidewise bending of crane by using total station |
| WO2023071774A1 (en) * | 2021-10-26 | 2023-05-04 | 山东神力索具有限公司 | Data processing method and apparatus for addition of load applying body, and electronic device |
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| CN115218804A (en) * | 2022-07-13 | 2022-10-21 | 长春理工大学中山研究院 | Fusion measurement method for multi-source system of large-scale component |
| CN115526918A (en) * | 2022-09-21 | 2022-12-27 | 上海市机械施工集团有限公司 | Structural deformation detection method, system, device, electronic equipment and medium |
| CN116839504A (en) * | 2023-07-28 | 2023-10-03 | 江苏省特种设备安全监督检验研究院 | Detection and early warning method and system for camber of crane |
| CN117053718A (en) * | 2023-10-11 | 2023-11-14 | 贵州黔程弘景工程咨询有限责任公司 | Beam bottom linear model generation method based on beam bottom linear measurement |
| CN117053718B (en) * | 2023-10-11 | 2023-12-12 | 贵州黔程弘景工程咨询有限责任公司 | Beam bottom linear model generation method based on beam bottom linear measurement |
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