A laser diameter measuring sensor and system for steel wire rope flaw detection

Abstract

This invention relates to the field of intelligent sensor technology, specifically to a laser diameter measuring sensor and system for wire rope flaw detection, including a structural fatigue early warning module, a cross-sectional profile de-biasing module, a surface defect early warning module, a three-dimensional coordinate construction module, and a structural fatigue early warning module. In this invention, multiple sets of photosensitive arrays are arranged around the wire rope to extract one-dimensional coordinates of the shadow boundary. The coordinates are then mapped by translation using the geometric center point of a polygon to obtain the true external profile of the de-biased cross-section, thereby evaluating radial distance differences for early warning of minor surface defects. Furthermore, by using extreme feature points combined with longitudinal running speed and sampling timestamps to construct a three-dimensional coordinate set of peak vertices, and dynamically calculating the twist span deviation, this invention eliminates measurement errors caused by lateral swaying, accurately captures minor surface anomalies, and comprehensively monitors the deep structural untwisting fatigue of the wire rope, improving the accuracy of wire rope flaw detection and the timeliness of safety early warning.

Description

Technical Field

[0001] This invention relates to the field of intelligent sensor technology, and in particular to a laser diameter measuring sensor and system for wire rope flaw detection. Background Technology

[0002] The field of intelligent sensor technology mainly involves microelectromechanical systems (MEMS) with information acquisition, data processing, and communication functions. Their primary purpose is to perform signal conditioning and logical operations on sensed physical or chemical quantities through a built-in microprocessor. They are widely used in industrial automation, the Internet of Things (IoT), and aerospace industries. Among these, laser diameter sensors for wire rope flaw detection refer to measuring devices and supporting hardware used to monitor surface defects and diameter changes in wire ropes. They are mainly used in scenarios such as mine hoisting, cableway transportation, and lifting machinery to detect the structural integrity of operating wire ropes. Typically, electromagnetic induction technology or photoelectric scanning technology is used to collect data on the external contour of the wire rope and information on changes in internal magnetic flux.

[0003] Traditional diameter sensors for wire rope flaw detection, while capable of acquiring external contour data and internal magnetic flux change information of wire ropes using electromagnetic induction or photoelectric scanning technologies, suffer from several drawbacks when the wire rope is in dynamic operation and accompanied by macroscopic lateral oscillation. These problems include easily distorted cross-sectional contour data, low accuracy in identifying minute surface defects, and difficulty in quantifying and analyzing the fatigue state of the three-dimensional structure. Summary of the Invention

[0004] To address the technical problems existing in the prior art, this invention provides a laser diameter measuring sensor and system for wire rope flaw detection. The technical solution is as follows:

[0005] On the one hand, a laser diameter measuring sensor and system for wire rope flaw detection is provided, including multiple sets of photosensitive array receivers arranged around the wire rope:

[0006] The boundary coordinate extraction module acquires the light intensity electrical signal value collected by the photosensitive array receiver, compares the light intensity electrical signal value with the preset light intensity reference threshold to determine the target photosensitive element position number, and outputs the photosensitive element position number as the one-dimensional coordinate value of the steel wire rope shadow boundary on the corresponding laser projection surface.

[0007] The cross-section profile de-biasing module extracts the one-dimensional coordinate values ​​of the wire rope shadow boundary to construct a polygonal two-dimensional coordinate set. It then analyzes the polygonal two-dimensional coordinate set through a polygonal profile feature extraction model to extract the two-dimensional coordinates of the geometric center point that characterizes the macroscopic lateral swing state of the wire rope. Finally, it performs a translation transformation mapping on the polygonal two-dimensional coordinates to obtain a set of two-dimensional coordinate data of the true cross-section external profile of the wire rope for de-biasing.

[0008] The surface defect early warning module extracts the internal coordinate points from the two-dimensional coordinate data set of the true cross-section of the deflection of the wire rope, evaluates the characteristic parameters of the difference in the radial distance between the contour coordinate points and the reference coordinate points of the wire rope, compares them with the preset surface defect tolerance threshold, and constructs an alarm electrical signal command for the surface micro-defects of the wire rope.

[0009] The three-dimensional coordinate construction module extracts the radial distance extreme value feature points from the two-dimensional coordinate data set of the true cross-section of the deflection of the steel wire rope as the two-dimensional coordinates of the protrusion apex. It integrates the acquired longitudinal running speed digital signal, sampling timestamp, and the two-dimensional coordinates of the protrusion apex through the three-dimensional spiral trajectory mapping model to construct a three-dimensional coordinate set of the crest apex of the steel wire rope.

[0010] The structural fatigue early warning module acquires the three-dimensional coordinate set of the peak vertices of the wire rope corresponding to adjacent time points, extracts the dynamic twist span characteristic parameters, calculates the twist deviation parameters between the twist span and the design standard, compares them with the preset structural failure tolerance threshold, and issues a wire rope structural untwisting fatigue early warning command signal.

[0011] As a further aspect of the present invention, during the process of determining the target photosensitive element position number, when the light intensity electrical signal value is greater than the preset light intensity reference threshold, it is determined that the corresponding photosensitive element is in the light-receiving area; when the light intensity electrical signal value is less than or equal to the preset light intensity reference threshold, it is determined that the corresponding photosensitive element is in the occlusion area, and the photosensitive element position number corresponding to the boundary between the light-receiving area and the occlusion area is extracted.

[0012] As a further aspect of the present invention, during the comparison with the preset surface defect tolerance threshold, when the cross-sectional radial distance difference characteristic parameter is greater than the preset surface defect tolerance threshold, the corresponding target coordinate point position information is extracted and the alarm electrical signal command for the minor surface defect of the wire rope is constructed; when the cross-sectional radial distance difference characteristic parameter is less than or equal to the preset surface defect tolerance threshold, it is determined that the cross-sectional profile of the wire rope is in good condition.

[0013] As a further aspect of the present invention, during the comparison with the preset structural failure tolerance threshold, when the twist deviation parameter is greater than the preset structural failure tolerance threshold, an early warning signal for the untwisting fatigue of the wire rope structure is issued; when the twist deviation parameter is less than or equal to the preset structural failure tolerance threshold, the overall torsional state of the wire rope is determined to be safe.

[0014] As a further aspect of the present invention, the boundary coordinate extraction module includes:

[0015] The light intensity numerical acquisition submodule acquires the light intensity electrical signal values ​​collected by each set of photosensitive array receivers arranged around the steel wire rope during the longitudinal movement of the steel wire rope, records the changes in the peak value of the light intensity electrical signal, compares the difference between the light intensity electrical signal value and the light intensity reference threshold, extracts the deviation of the difference between the two, and generates light intensity difference amplitude feature data.

[0016] The light-receiving state determination submodule, based on the light intensity difference amplitude characteristic data, determines that when the light intensity electrical signal value is greater than the preset light intensity reference threshold, the corresponding photosensitive element is in the light-receiving area, and when the light intensity electrical signal value is less than or equal to the preset light intensity reference threshold, the corresponding photosensitive element is in the occlusion area. It records and compiles all photosensitive element area distribution location information to obtain the photosensitive element light-receiving state distribution set.

[0017] The boundary coordinate output submodule analyzes the jump situation between adjacent intervals of each element based on the light-receiving state distribution set of the photosensitive element, extracts the target photosensitive element position number at the boundary between the light-receiving area and the occluded area, maps the target photosensitive element position number into a linearly arranged one-dimensional coordinate value based on the projection relationship of the laser projection surface, and outputs the dynamic change of the shadow position in combination with the time dimension parameter of the sampling time, and establishes the one-dimensional coordinate value of the steel wire rope shadow boundary.

[0018] As a further aspect of the present invention, the cross-sectional profile correction module includes:

[0019] The contour coordinate mapping submodule obtains the corresponding one-dimensional values ​​of all receiver outputs at the same sampling time based on the one-dimensional coordinate values ​​of the steel wire rope shadow boundary, extracts the installation angle relationship of the laser transmitter, and uses the angle transformation matrix to uniformly translate and map the one-dimensional coordinate values ​​of the steel wire rope shadow boundary to the same two-dimensional rectangular coordinate system. It then compiles all coordinate points to construct the vertex set of the outer perimeter of the occlusion area and generates a polygonal two-dimensional coordinate set.

[0020] The geometric center extraction submodule extracts the horizontal and vertical coordinate parameters of all vertices based on the polygon's two-dimensional coordinate set. It performs vertex summation and average calculation on all coordinate parameters to extract polygon contour feature components. It analyzes the coordinate distribution of each outer vertex of the polygon to obtain the geometric centroid parameter of the overall closed region. It assigns the horizontal and vertical components of the centroid parameter to the corresponding spatial geometric positioning point to obtain the two-dimensional coordinates of the geometric center point.

[0021] The contour coordinate de-biasing module extracts the lateral deviation offset based on the two-dimensional coordinates of the geometric center point, performs a reverse translation transformation mapping operation on all vertices in the polygon two-dimensional coordinate set, deducts the lateral offset component between the geometric center and the origin from the vertex x-coordinates, eliminates the coordinate data distortion caused by the lateral swing motion trajectory of the wire rope, and establishes a set of two-dimensional coordinate data of the true external contour of the wire rope de-biasing section.

[0022] As a further aspect of the present invention, the surface defect early warning module includes:

[0023] The coordinate polar angle matching submodule extracts the contour coordinate points from the two-dimensional coordinate data set of the true cross-section of the deflected wire rope, establishes a two-dimensional reference coordinate set of the standard cross-section based on the calibration of the intact wire rope, performs polar angle position feature matching calculation on the contour coordinate points and the coordinate points in the two-dimensional reference coordinate set of the standard cross-section, filters and extracts the reference coordinate points with the same polar angle position, and obtains the set of polar angle matching coordinate points of the wire rope.

[0024] The radial distance evaluation submodule extracts position parameters from the contour coordinate points and corresponding reference coordinate points within the set of polar angle matching coordinate points of the wire rope, calculates the straight line length between the two coordinate points according to Euclidean distance, evaluates the radial distance deviation difference between the contour coordinate points and the reference points, compiles all point-to-point distance differences and converts them into feature quantities, and obtains the cross-sectional radial distance difference feature parameters.

[0025] The defect alarm generation submodule extracts numerical features based on the cross-sectional radial distance difference feature parameter, compares the cross-sectional radial distance difference feature parameter with the numerical range limit of the preset surface defect tolerance threshold, and extracts the position information of the corresponding target coordinate point when the cross-sectional radial distance difference feature parameter is greater than the surface defect tolerance threshold, and generates an electrical signal command for alarming minor defects on the surface of the wire rope.

[0026] As a further aspect of the present invention, the three-dimensional coordinate construction module includes:

[0027] The vertex coordinate extraction submodule analyzes the radial distribution distance characteristics of the outer contour coordinate points in the two-dimensional rectangular coordinate system region based on the two-dimensional coordinate data set of the true cross-section of the deflected wire rope. It compares the radial distances in various directions to extract the extreme radial distance feature points in the outward convex state and uses the horizontal and vertical coordinate parameters of the extreme feature points as the outer edge vertices of each strand of the wire rope to obtain the two-dimensional coordinates of the convex vertex.

[0028] The longitudinal displacement integration submodule determines the relative position of the current plane in the spatial plane based on the two-dimensional coordinates of the protrusion vertex. During continuous operation sampling, it collects digital signals of longitudinal running speed representing the longitudinal running state of the wire rope and corresponding sampling timestamps. It integrates the digital signals of longitudinal running speed with the corresponding interval sampling timestamps to perform product integration to calculate the cumulative actual distance of unidirectional running and generate the absolute longitudinal displacement feature dimension.

[0029] The three-dimensional coordinate splicing submodule extracts the components of the two-dimensional coordinates of the protrusion vertex and the absolute longitudinal displacement feature dimension. It takes the absolute longitudinal displacement feature dimension as the axial value of the longitudinal coordinate system in the spatial coordinate axis and performs spatial geometric dimension splicing and combination calculation with the cross-sectional horizontal and vertical values ​​represented by the two-dimensional coordinates of the protrusion vertex. It then assembles the spliced ​​vertex spatial position parameters to construct a spiral extension trajectory set and establishes a three-dimensional coordinate set of the crest vertex of the wire rope.

[0030] As a further aspect of the present invention, the structural fatigue early warning module includes:

[0031] The twist span extraction submodule extracts internal three-dimensional spatial points based on the three-dimensional coordinate set of the crests of the wire rope corresponding to two adjacent sampling times. It analyzes the longitudinal difference parameter of the spatial distribution span of the three-dimensional coordinate set of the crests of the wire rope in the longitudinal coordinate axis direction at two adjacent times, extracts the dynamic twist span change amount that characterizes the change state of the twist span crest spacing of the wire rope, and obtains the dynamic twist span feature parameter.

[0032] The twist deviation calculation submodule extracts the dynamic span distance feature value based on the dynamic twist span feature parameter, obtains the design standard twist span benchmark set in advance according to the design index of the wire rope factory parameters, calculates the distribution of the absolute span difference between the dynamic twist span feature parameter and the design standard twist span benchmark, evaluates the overall offset feature value of structural deformation during operation, and obtains the twist deviation parameter.

[0033] The fatigue early warning judgment submodule extracts the deformation deviation value based on the twist deviation parameter, compares the twist deviation parameter with the range of the preset structural failure tolerance threshold value, triggers an alarm action when the twist deviation parameter is determined to be greater than the preset structural failure tolerance threshold, summarizes the detection result data and fault point parameters and generates alarm information, and establishes a wire rope structure untwisting fatigue early warning command signal.

[0034] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following:

[0035] By arranging multiple photosensitive arrays around the wire rope to extract the one-dimensional coordinates of the shadow boundary, and using the geometric center point of the polygon to perform a translation transformation mapping on the coordinates to obtain the true external contour of the cross-section after de-biasing, the radial distance difference characteristics are evaluated to provide early warning of minor surface defects. At the same time, by using extreme feature points combined with longitudinal running speed and sampling timestamps to construct a three-dimensional coordinate set of wave crests and apexes, and dynamically calculating the twist span deviation, high-fidelity restoration of the true cross-sectional dimensions of the running wire rope is achieved. This eliminates measurement errors caused by lateral sway, accurately captures minor surface anomalies, and comprehensively monitors the deep structural untwisting fatigue of the wire rope, improving the accuracy of wire rope flaw detection and the timeliness of safety early warning. Attached Figure Description

[0036] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0037] Figure 1 This is a schematic diagram of a laser diameter measuring sensor and system for wire rope flaw detection provided in an embodiment of the present invention;

[0038] Figure 2 This is a schematic diagram of the system framework of the present invention;

[0039] Figure 3 This is a flowchart of the boundary coordinate extraction module of the present invention;

[0040] Figure 4 This is a flowchart of the cross-sectional contour de-eccentrication module of the present invention;

[0041] Figure 5 This is a flowchart of the surface defect early warning module of the present invention;

[0042] Figure 6 This is a flowchart of the three-dimensional coordinate construction module of the present invention;

[0043] Figure 7 This is a flowchart of the structural fatigue early warning module of the present invention. Detailed Implementation

[0044] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0045] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0046] This invention provides a laser diameter measuring sensor and system for wire rope flaw detection, such as... Figure 1-2 The laser diameter measuring sensor shown is used for flaw detection of steel wire ropes. The sensor includes multiple photosensitive array receivers arranged around the periphery of the steel wire rope, including:

[0047] The boundary coordinate extraction module acquires the light intensity electrical signal value collected by the photosensitive array receiver, compares the light intensity electrical signal value with the preset light intensity reference threshold to determine the target photosensitive element position number, and outputs the photosensitive element position number as the one-dimensional coordinate value of the steel wire rope shadow boundary on the corresponding laser projection surface.

[0048] Among them, the preset light intensity reference threshold refers to the light intensity reference threshold calibrated in an unloaded lighting environment;

[0049] The cross-section contour de-biasing module obtains the one-dimensional coordinate values ​​of all wire rope shadow boundaries at the same sampling time. Based on the installation angle relationship of the laser emitter, the one-dimensional coordinate values ​​of the wire rope shadow boundaries are uniformly mapped to a two-dimensional rectangular coordinate system to construct a polygonal two-dimensional coordinate set representing the wire rope occlusion contour. The polygonal contour feature extraction model is used to analyze the polygonal two-dimensional coordinate set to extract the two-dimensional coordinates of the geometric center point representing the macroscopic lateral swing state of the wire rope. The polygonal two-dimensional coordinates are translated and mapped to obtain the two-dimensional coordinate data set of the true cross-section external contour of the de-biased wire rope.

[0050] The surface defect early warning module extracts the internal coordinate points from the two-dimensional coordinate data set of the true cross-section of the wire rope, evaluates the characteristic parameters of the difference in the radial distance between the contour coordinate points and the reference coordinate points of the wire rope, compares them with the preset surface defect tolerance threshold, and constructs an alarm electrical signal command for minor surface defects of the wire rope.

[0051] Among them, the preset surface defect tolerance threshold refers to the surface defect tolerance threshold set by the national steel wire rope flaw detection industry standard;

[0052] The 3D coordinate construction module extracts the radial distance extreme value feature points from the 2D coordinate data set of the true cross-section of the wire rope as the 2D coordinates of the convex vertex. It integrates the acquired longitudinal running speed digital signal, sampling timestamp, and 2D coordinates of the convex vertex through the 3D spiral trajectory mapping model to construct a 3D coordinate set of the convex vertex of the wire rope wave crest.

[0053] The structural fatigue early warning module acquires the three-dimensional coordinate set of the peak of the wire rope at adjacent times, extracts the dynamic twist span characteristic parameters, calculates the twist deviation parameters between the design standard twist span benchmark and the preset structural failure tolerance threshold, and issues a wire rope structure untwisting fatigue early warning command signal.

[0054] The standard lay span is set by the wire rope factory parameters; the preset structural failure tolerance threshold refers to the structural failure tolerance threshold set according to the national flaw detection industry standards and the wire rope factory parameters.

[0055] The one-dimensional coordinate values ​​of the wire rope shadow boundary include the position of the left shadow edge point and the position of the right shadow edge point; the two-dimensional coordinate data set of the actual cross-section of the wire rope includes the actual contour lateral relative coordinates and the actual contour longitudinal relative coordinates; the alarm electrical signal commands for minor defects on the wire rope surface include the defect severity warning code and the wear orientation indication code; the three-dimensional coordinate set of the wire rope crest apex includes the strand crest spatial depth coordinates, strand crest spatial height coordinates, and strand crest longitudinal distribution coordinates; the wire rope structural untwisting fatigue early warning command signals include the strand loosening danger warning signal and the abnormal deformation emergency alarm signal.

[0056] Specifically, such as Figure 2 , 3 As shown, the boundary coordinate extraction module includes:

[0057] The light intensity numerical acquisition submodule acquires the light intensity electrical signal values ​​collected by each set of photosensitive array receivers arranged around the steel wire rope during the longitudinal movement of the steel wire rope, records the changes in the peak value of the light intensity electrical signal, compares the difference between the light intensity electrical signal value and the light intensity reference threshold, extracts the deviation of the difference between the two, and generates light intensity difference amplitude feature data.

[0058] Within the overall architecture of the wire rope flaw detection system, this device, as a crucial front-end sensing component, is linked to a high-resolution laser diameter measuring sensor to provide a high-precision light source reference. The light intensity numerical acquisition submodule reads the light intensity electrical signal values ​​collected in real time from eight sets of photosensitive array receivers arranged around the wire rope via a serial communication interface. This module converts the continuous analog electrical signal output by each photosensitive unit in each set of photosensitive arrays into discrete digital light intensity electrical signal values ​​through an internal analog-to-digital converter circuit, with a sampling frequency set to 1000 Hz. The light intensity numerical acquisition submodule continuously extracts the light intensity electrical signal values ​​within a time series, performs differential calculations on the digital light intensity electrical signal values ​​at adjacent time points, and records the turning point where the difference result changes from positive to negative as the peak of the light intensity electrical signal value. This module then obtains a preset light intensity reference threshold, which is determined by multiplying the reference light intensity value under unobstructed conditions by a scaling factor of 0.8. For example, if the reference light intensity value under unobstructed conditions is 500 milliwatts per square centimeter, then the preset light intensity reference threshold is 400 milliwatts per square centimeter. The light intensity numerical acquisition submodule compares the currently extracted digital light intensity electrical signal value with a preset light intensity reference threshold, performing a difference calculation. Specifically, it subtracts the preset light intensity reference threshold from the current digital light intensity electrical signal value and extracts the deviation magnitude of the difference. For example, if the current digital light intensity electrical signal value is 450 milliwatts per square centimeter and the preset light intensity reference threshold is 400 milliwatts per square centimeter, the difference calculation yields a deviation magnitude of 50 milliwatts per square centimeter. The light intensity numerical acquisition submodule then arranges the difference deviation magnitudes of all photosensitive units within the same sampling period sequentially by array number and unit sequence number, generating light intensity difference magnitude feature data.

[0059] The light-receiving state determination submodule, based on the light intensity difference amplitude characteristic data, determines that when the light intensity electrical signal value is greater than the preset light intensity reference threshold, the corresponding photosensitive element is in the light-receiving area, and when the light intensity electrical signal value is less than or equal to the preset light intensity reference threshold, the corresponding photosensitive element is in the occlusion area. It records and compiles the distribution location information of all photosensitive element regions to obtain the light-receiving state distribution set of photosensitive elements.

[0060] The light-receiving state determination submodule receives light intensity difference amplitude characteristic data and iterates through the digital light intensity electrical signal values ​​corresponding to each photosensitive element. This module executes conditional branch judgment logic: when the light intensity electrical signal value of a photosensitive element is detected to be greater than a preset light intensity reference threshold, a status code 1 is assigned to that photosensitive element, marking it as being in the light-receiving area; when the light intensity electrical signal value of a photosensitive element is detected to be less than or equal to the preset light intensity reference threshold, a status code 0 is assigned to that photosensitive element, marking it as being in the occluded area. For example, if the preset light intensity reference threshold is 400 milliwatts per square centimeter, and the light intensity electrical signal value of one photosensitive element is 450 milliwatts per square centimeter (greater than 400 milliwatts per square centimeter), the light-receiving state determination submodule assigns it status code 1; if the light intensity electrical signal value of another photosensitive element is 150 milliwatts per square centimeter (less than 400 milliwatts per square centimeter), the module assigns it status code 0. The light-receiving state determination submodule extracts the row and column numbers of the physical arrangement of each photosensitive element in the array, records and compiles the row and column numbers of all photosensitive elements and their corresponding status codes, and constructs a two-dimensional data matrix. This module stores the two-dimensional data matrix as the location information of the photosensitive element region, thereby obtaining a set of photosensitive element light-receiving state distribution containing the coordinates of all photosensitive units and their light-receiving status codes.

[0061] The boundary coordinate output submodule analyzes the jump between adjacent intervals of each element based on the distribution set of the light-receiving state of the photosensitive element, extracts the position number of the target photosensitive element at the boundary between the light-receiving area and the occluded area, maps the position number of the target photosensitive element into linearly arranged one-dimensional coordinate values ​​based on the projection relationship of the laser projection surface, and outputs the dynamic change of the shadow position by combining the time dimension parameter of the sampling time, and establishes the one-dimensional coordinate value of the steel wire rope shadow boundary.

[0062] The boundary coordinate output submodule extracts a two-dimensional data matrix from the set of light-receiving state distributions of the photosensitive elements, comparing the status codes of adjacent photosensitive elements along the row direction. This module records the transitions between adjacent intervals where the status code changes from 1 to 0 or from 0 to 1, and extracts the target photosensitive element position number corresponding to the boundary where the status code transition occurs. For example, if the status code of element 15 is 1 and the status code of element 16 is 0, then position numbers 15 and 16 are extracted as the target photosensitive element position numbers. The boundary coordinate output submodule obtains the installation height and projection angle of the laser emitter integrated inside the laser diameter sensor, and maps the target photosensitive element position numbers into linearly arranged one-dimensional coordinate values ​​based on the projection relationship of the laser projection surface. The conversion method is to multiply the position number by the physical size of a single photosensitive element and add a trigonometric function compensation value based on the projection angle. For example, if the position number is 15, the size of a single element is 2 mm, and the trigonometric function compensation value is 5 mm, then the product is 30 mm, and adding 5 mm gives a linearly arranged one-dimensional coordinate value of 35 mm. The boundary coordinate output submodule extracts the time dimension parameter generated by the crystal oscillator inside the sampling device at the current sampling moment, encapsulates the linearly arranged one-dimensional coordinate values ​​with the time dimension parameter, and outputs the dynamic changes in the shadow position. This module connects multiple linearly arranged one-dimensional coordinate values ​​extracted at the same time in spatial order to establish one-dimensional coordinate values ​​of the wire rope shadow boundary that reflect the current outer contour state of the cross-section and provide a precise geometric benchmark for subsequent wire rope flaw detection.

[0063] Specifically, such as Figure 2 , 4 As shown, the cross-sectional profile correction module includes:

[0064] The contour coordinate mapping submodule obtains the corresponding one-dimensional values ​​of all receiver outputs at the same sampling time based on the one-dimensional coordinate values ​​of the wire rope shadow boundary. It extracts the installation angle relationship of the laser transmitter and uses the angle transformation matrix to uniformly translate and map the one-dimensional coordinate values ​​of the wire rope shadow boundary to the same two-dimensional rectangular coordinate system. It compiles all coordinate points to construct the vertex set of the outer perimeter of the occlusion area and generates a polygonal two-dimensional coordinate set.

[0065] The contour coordinate mapping submodule extracts the one-dimensional coordinate values ​​of the wire rope shadow boundary at the same sampling time and retrieves the corresponding one-dimensional values ​​from all receiver outputs in the sensor configuration library. This module obtains the pitch and yaw angle parameters from the laser transmitter installation angle relationship, constructs an angle transformation matrix based on these parameters, and the internal elements of the angle transformation matrix consist of the cosine of the pitch angle and the sine of the yaw angle. The contour coordinate mapping submodule constructs the one-dimensional coordinate values ​​of the wire rope shadow boundary as a column vector, performs matrix multiplication on this column vector using the angle transformation matrix, and uses the product as the translated coordinates, thus uniformly translating and mapping all the one-dimensional coordinate values ​​of the wire rope shadow boundary to the same two-dimensional Cartesian coordinate system. For example, if the one-dimensional coordinate value of the wire rope shadow boundary is 35 mm, the corresponding receiver installation radius is 100 mm, the cosine of the pitch angle is 0.8, and the sine of the yaw angle is 0.6, this module, through matrix operations, obtains a mapped x-coordinate of 80 mm and a y-coordinate of 60 mm.

[0066] Table 1 Example Table of Mapping Parameters

[0067]

[0068] As shown in Table 1, the contour coordinate mapping submodule assembles all the transformed horizontal and vertical coordinate points to construct the vertex set of the outer perimeter of the occluded area, and sorts these vertices in a clockwise direction to generate a polygonal two-dimensional coordinate set.

[0069] The geometric center extraction submodule extracts the horizontal and vertical coordinate parameters of all vertices based on the polygon's two-dimensional coordinate set. It performs vertex summation and average calculation on all coordinate parameters to extract polygon contour feature components. It analyzes the coordinate distribution of each outer vertex of the polygon to obtain the geometric centroid parameter of the overall closed region. It assigns the horizontal and vertical components of the centroid parameter to the corresponding spatial geometric positioning point to obtain the two-dimensional coordinates of the geometric center point.

[0070] The geometry center extraction submodule traverses the polygon's 2D coordinate set, extracting the horizontal and vertical coordinate parameters of each vertex. This module sums the horizontal coordinate parameters of all vertices and independently sums the vertical coordinate parameters. The geometry center extraction submodule calculates the total number of vertices on the polygon's perimeter, sums the horizontal coordinate parameters and divides the sum by the total number to obtain the horizontal component of the centroid parameter, and sums the vertical coordinate parameters and divides the sum by the total number to obtain the vertical component of the centroid parameter. This vertex summation and averaging operation extracts the polygon's contour feature components. For example, if the polygon's 2D coordinate set contains 100 vertices, and the sum of the horizontal coordinate parameters is 5000 mm and the sum of the vertical coordinate parameters is 6000 mm, this module divides 5000 mm by 100 to obtain a 50 mm horizontal component of the centroid parameter and divides 6000 mm by 100 to obtain a 60 mm vertical component of the centroid parameter. The geometric center extraction submodule analyzes the coordinate distribution of each outer vertex of the polygon to obtain the geometric centroid parameters of the entire closed region. The calculated horizontal and vertical components of the centroid parameters are then used as the geometric centroid parameters of the entire closed region. This module assigns the corresponding horizontal and vertical components of the centroid parameters to spatial geometric positioning points, thereby obtaining the two-dimensional coordinates of the geometric center point.

[0071] The contour coordinate de-biasing module extracts the lateral deviation offset based on the two-dimensional coordinates of the geometric center point, performs a reverse translation transformation mapping operation on all vertices in the polygon two-dimensional coordinate set, deducts the lateral offset component between the geometric center and the origin from the vertex x-coordinate, eliminates the coordinate data distortion caused by the lateral swing motion trajectory of the wire rope, and establishes a set of two-dimensional coordinate data of the true external contour of the wire rope de-biasing section.

[0072] The contour coordinate de-biasing module retrieves the 2D coordinates of the geometric center point and extracts its lateral component as the lateral offset. This module iterates through the lateral coordinate parameters of all vertices in the polygon 2D coordinate set, performing a reverse translation transformation on all vertices. Specifically, it subtracts the lateral offset component between the geometric center and the origin from the lateral coordinate parameter of each vertex; that is, the difference between the lateral component of the geometric center point and the lateral component of the ideal center origin. For example, if the lateral coordinate of the ideal center origin is 0 mm and the lateral coordinate of the geometric center point is 50 mm, then the lateral offset is 50 mm. For a vertex in the polygon 2D coordinate set with a lateral coordinate of 80 mm, the contour coordinate de-biasing module subtracts 50 mm from 80 mm, resulting in a reverse-translated lateral coordinate of 30 mm. This module performs this subtraction operation on the lateral coordinate of every vertex in the set, eliminating coordinate data distortion caused by the lateral swing trajectory of the wire rope, while keeping the ordinate unchanged or performing corresponding vertical de-biasing processing. The contour coordinate de-biasing module recombines and pairs the x-coordinates and y-coordinates of all vertices that have completed the reverse translation calculation, and establishes a set of two-dimensional coordinate data of the true external contour of the wire rope de-biasing section.

[0073] Specifically, such as Figure 2 , 5 As shown, the surface defect early warning module includes:

[0074] The polar angle matching submodule extracts the contour coordinate points from the two-dimensional coordinate data set of the true external contour of the wire rope deflection, establishes a two-dimensional reference coordinate set of the standard section based on the calibration of the intact wire rope, performs polar angle position feature matching calculation on the contour coordinate points and the coordinate points in the two-dimensional reference coordinate set of the standard section, filters and extracts the reference coordinate points with the same polar angle position, and obtains the set of polar angle matching coordinate points of the wire rope.

[0075] The polar angle matching submodule extracts the horizontal and vertical parameters of all contour coordinate points from the two-dimensional coordinate data set of the true cross-section of the wire rope. This module calls the standard cross-section two-dimensional reference coordinate set established based on the calibration of the intact wire rope. It divides the vertical coordinate of each contour coordinate point by its horizontal coordinate to obtain the tangent value, and then calculates the actual polar angle value corresponding to each contour coordinate point using the arctangent function. Simultaneously, the polar angle matching submodule uses the same arctangent function to calculate the reference polar angle values ​​of coordinate points within the standard cross-section two-dimensional reference coordinate set. This module calculates the difference between the polar angle value of the contour coordinate point and the reference polar angle value, determining that point pairs with an absolute difference less than or equal to 0.05 radians possess polar angle position feature matching attributes. For example, if a contour coordinate point has an horizontal coordinate of 30 mm and a vertical coordinate of 40 mm, its actual polar angle value is calculated to be 0.927 radians. If there is a reference coordinate point in the standard cross-section two-dimensional reference coordinate set with a polar angle of 0.930 radians, the absolute difference between the two is 0.003 radians, which is less than 0.05 radians. Therefore, the polar angle matching submodule determines that the polar angle position feature matching calculation has been completed. This module filters and extracts all reference coordinate points and their corresponding contour coordinate points with the same polar angle position, and arranges them in pairs to obtain the set of steel wire rope polar angle matching coordinate points.

[0076] The radial distance assessment submodule extracts position parameters between the contour coordinate points and the corresponding reference coordinate points within the set of polar angle matching coordinate points of the wire rope, calculates the straight line length between the two coordinate points according to Euclidean distance, assesses the magnitude of the radial distance deviation difference between the contour coordinate points and the reference points, compiles all point-to-point distance differences and converts them into feature quantities, and obtains the cross-sectional radial distance difference feature parameters.

[0077] The radial distance assessment submodule extracts the lateral and longitudinal position parameters of the contour coordinate points and the corresponding reference coordinate points within the wire rope polar angle matching coordinate point set. This module calculates the straight-line length between the two coordinate points using Euclidean distance, specifically calculating the actual radial distance between the contour coordinate point and the origin, and the reference radial distance between the corresponding reference coordinate point and the origin. The radial distance assessment submodule subtracts the reference radial distance from the actual radial distance and obtains the absolute value, evaluating the magnitude of the radial distance deviation between the contour coordinate point and the reference point. This deviation magnitude and distance resolution are core indicators for assessing the degree of surface wear during wire rope flaw detection.

[0078] Table 2 Radial Distance Deviation Analysis Table

[0079]

[0080] As shown in Table 2, the actual radial distance between the contour coordinate points is 50.0 mm, and the reference radial distance is 50.5 mm. This module calculates the absolute difference between the two to be 0.5 mm, which is the magnitude of the radial distance deviation. The radial distance evaluation submodule performs the above absolute difference calculation point by point, compiles all point-to-point distance differences, and arranges them into a one-dimensional array. This one-dimensional array is then converted into a feature quantity, reflecting the current cross-sectional state. This module calculates the maximum and average values ​​of all distance differences within the one-dimensional array, encapsulates the maximum and average values, and obtains the cross-sectional radial distance difference feature parameter.

[0081] The defect alarm generation submodule extracts numerical features based on the cross-sectional radial distance difference feature parameter, compares the cross-sectional radial distance difference feature parameter with the preset surface defect tolerance threshold value range, and extracts the corresponding target coordinate point position information when the cross-sectional radial distance difference feature parameter is greater than the surface defect tolerance threshold, and generates a wire rope surface micro-defect alarm electrical signal command.

[0082] The defect alarm generation submodule reads the radial distance difference feature parameters of the cross-section and extracts numerical features such as the maximum and average distance difference values. This module retrieves the preset surface defect tolerance threshold value range from memory. The preset surface defect tolerance threshold is determined by the upper limit of the 95% confidence interval of normal wire rope wear history data, specifically set to 1.5 mm. The defect alarm generation submodule compares the maximum value in the radial distance difference feature parameters of the cross-section with the preset surface defect tolerance threshold, executing a numerical relationship judgment logic. For example, if the maximum value in the aforementioned radial distance difference feature parameters is 1.8 mm and the preset surface defect tolerance threshold is 1.5 mm, the module determines that 1.8 mm is greater than 1.5 mm. When the radial distance difference feature parameters of the cross-section are greater than the surface defect tolerance threshold, the defect alarm generation submodule extracts the target coordinate point location information corresponding to the maximum difference, i.e., the x-coordinate and y-coordinate of the point in the two-dimensional coordinate system, as well as the corresponding polar angle information. This module packages the target coordinate point location information and the difference between the out-of-limit values ​​into a data frame with a specific communication format, sends a high-level trigger pulse to the control port of the peripheral device, and generates an alarm electrical signal command for minor defects on the surface of the wire rope, thereby completing the automatic identification and early warning closed loop of surface anomalies in the wire rope flaw detection process.

[0083] Specifically, such as Figure 2 , 6 As shown, the 3D coordinate construction module includes:

[0084] The vertex coordinate extraction submodule analyzes the radial distribution distance characteristics of the outer contour coordinate points in the two-dimensional rectangular coordinate system region based on the two-dimensional coordinate data set of the true cross-section of the wire rope after deflection. It compares the radial distance in each direction to extract the extreme radial distance feature points in the outward convex state and uses the horizontal and vertical coordinate parameters of the extreme feature points as the outer edge vertices of each strand of the wire rope to obtain the two-dimensional coordinates of the convex vertex.

[0085] The vertex coordinate extraction submodule receives a set of two-dimensional coordinate data of the outer contour of the true cross-section of the wire rope and calculates the radial distance parameter from each outer contour coordinate point to the origin. This module analyzes the radial distribution distance characteristics of the outer contour coordinate points in a two-dimensional rectangular coordinate system region, comparing the radial distances of adjacent contour coordinate points in various directions of the circumference. The accuracy of this radial distance parameter calculation directly depends on the dynamic acquisition frequency and calibration accuracy of the front-end laser diameter measuring sensor. The vertex coordinate extraction submodule compares the radial distances between three adjacent points in a clockwise direction. When the radial distance of the middle coordinate point is simultaneously greater than the radial distances of its two adjacent coordinate points on either side, this middle coordinate point is extracted as an extreme radial distance feature point in an outward convex state. For example, if the radial distances of three adjacent coordinate points are 25 mm, 28 mm, and 26 mm respectively, the module compares and finds that 28 mm is greater than the values ​​on either side, extracting this point as an extreme feature point. The vertex coordinate extraction submodule uses the horizontal and vertical coordinate parameters of all extreme feature points as the outer vertices of each strand of the wire rope, filters out redundant interfering feature points according to the standard wire rope strand count, and retains several feature points with the largest radial distances. This module encapsulates the horizontal and vertical parameters of these filtered feature points into a matrix, ultimately obtaining the two-dimensional coordinates of all protrusion vertices.

[0086] The longitudinal displacement integration submodule determines the relative position of the current plane in the spatial plane based on the two-dimensional coordinates of the protrusion vertex. During continuous sampling, it collects digital signals of longitudinal running speed representing the longitudinal running state of the wire rope and corresponding sampling timestamps. It integrates the digital signals of longitudinal running speed with the corresponding interval sampling timestamps to calculate the cumulative actual distance of unidirectional running and generates the absolute longitudinal displacement feature dimension.

[0087] The longitudinal displacement integration submodule determines the relative position of the current plane in space based on the two-dimensional coordinates of the convex vertex and continuously receives digital pulse signals from the speed encoder. During continuous sampling, this module converts the pulse frequency into a digital signal representing the longitudinal running speed of the wire rope, and simultaneously calls the system clock module to obtain the corresponding sampling timestamp. The longitudinal displacement integration submodule calculates the time difference parameter between two adjacent sampling timestamps and integrates the longitudinal running speed digital signal with the time difference parameter of the corresponding interval for product integration. Specifically, the calculation process uses the trapezoidal integral rule to sum the speed digital signals of the current moment and the previous moment, divides by 2, and then multiplies by the time difference parameter to obtain the cumulative actual distance of unidirectional running. For example, if the speed at the previous moment was 5.0 meters per second and the speed at the current moment is 5.2 meters per second, with a time difference of 0.1 seconds, this module adds 5.0 and 5.2 to get 10.2, divides by 2 to get 5.1 meters per second, and multiplies by 0.1 seconds to get 0.51 meters. The longitudinal displacement integration submodule accumulates the distance values ​​of each interval to generate the absolute longitudinal displacement feature dimension from the initial zero point to the current sampling time.

[0088] The three-dimensional coordinate splicing submodule extracts the components of the two-dimensional coordinates of the protrusion vertex and the absolute longitudinal displacement feature dimension. The absolute longitudinal displacement feature dimension is used as the axial value of the longitudinal coordinate system in the spatial coordinate axis. It performs spatial geometric dimension splicing and combination calculation with the two-dimensional coordinates of the protrusion vertex to represent the cross-sectional longitudinal and transverse values. The spliced ​​vertex spatial position parameters are assembled to construct a spiral extension trajectory set and establish a three-dimensional coordinate set of the crest vertex of the wire rope.

[0089] The 3D coordinate stitching submodule extracts the individual components of the 2D coordinates of the protruding vertices generated by the vertex coordinate extraction submodule, and simultaneously extracts the individual components of the absolute longitudinal displacement feature dimension generated by the longitudinal displacement integration submodule. This module uses the absolute longitudinal displacement feature dimension as the longitudinal axis value of the Z-axis in the spatial rectangular coordinate system, and uses the x and y coordinates of the cross-section represented by the 2D coordinates of the protruding vertices as the values ​​of the X and Y axes in the spatial rectangular coordinate system, respectively. The 3D coordinate stitching submodule performs spatial geometric dimension stitching and combination operations, combining the X, Y, and Z axis values ​​obtained at each sampling moment into a one-dimensional array containing three elements. For example, if the lateral value of a protruding vertices is 30 mm, the longitudinal value is 40 mm, and the absolute longitudinal displacement at the current corresponding moment is 510 mm, this module stitches and combines these values ​​to obtain a one-dimensional array. The 3D coordinate stitching submodule compiles the spliced ​​vertex spatial position parameters at all moments in chronological order, and constructs a spiral extension trajectory set according to the strand number. This module stores all 3D data points in this trajectory set into a 3D data linked list, thereby establishing a 3D coordinate set of the crest vertices of the wire rope.

[0090] Specifically, such as Figure 2 , 7As shown, the structural fatigue early warning module includes:

[0091] The twist span extraction submodule extracts internal three-dimensional spatial points based on the three-dimensional coordinate set of the crests of the wire rope corresponding to two adjacent sampling times. It analyzes the longitudinal difference parameter of the spatial distribution span of the three-dimensional coordinate set of the crests of the wire rope in the longitudinal coordinate axis direction at two adjacent times, extracts the dynamic twist span change quantity that characterizes the change state of the twist span of the wire rope, and obtains the dynamic twist span characteristic parameter.

[0092] The lay span extraction submodule extracts the Z-axis coordinate components of internal three-dimensional spatial points based on the three-dimensional coordinate set of the wire rope crest apex corresponding to two adjacent sampling times. This module analyzes the spatial distribution span of the three-dimensional coordinate set of the wire rope crest apex corresponding to the same strand at two adjacent times along the longitudinal axis, calculating the difference parameter in the Z-axis direction between two adjacent crest extreme points of the same strand. The lay span extraction submodule traverses all crest points of a single strand throughout the entire detection period, subtracting the Z-axis coordinates of two adjacent crest extreme points to extract the dynamic lay span change, characterizing the change in the wire rope lay span distance between crests. For example, if the current crest apex Z-axis coordinate is 1210 mm and the previous adjacent crest apex Z-axis coordinate is 510 mm, this module subtracts 510 mm from 1210 mm, calculating a longitudinal difference of 700 mm in the spatial distribution span. The twist span extraction submodule performs median filtering on all calculated longitudinal differences, removes abrupt and abnormal difference data, and encapsulates the filtered and smoothed output wave peak spacing change numerical sequence to obtain the dynamic twist span feature parameters under the current running segment.

[0093] The twist deviation calculation submodule extracts the dynamic span distance feature value based on the dynamic twist span feature parameter, obtains the design standard twist span benchmark set in advance according to the design index of the wire rope factory parameters, calculates the distribution of the absolute span difference between the dynamic twist span feature parameter and the design standard twist span benchmark, evaluates the overall offset feature value of structural deformation during operation, and obtains the twist deviation parameter.

[0094] The lay deviation calculation submodule extracts specific dynamic span distance characteristic values ​​based on dynamic lay span characteristic parameters. This module retrieves the internal configuration database to obtain the design standard lay span benchmark, pre-set according to the wire rope's factory design parameters. This benchmark is directly derived from the rated lay length value in the factory inspection parameter table and is set to 710 mm. The lay deviation calculation submodule calculates the difference between the dynamic span distance characteristic value and the design standard lay span benchmark and obtains the absolute value, thus acquiring the distribution of the absolute span difference.

[0095] Table 3 Calculation Parameters for Twist Deviation

[0096]

[0097] As shown in Table 3, if the dynamic span distance characteristic value is 700 mm and the design standard twist pitch span benchmark is 710 mm, this module calculates the absolute value of the difference to obtain 10 mm. The twist pitch deviation calculation submodule calculates the arithmetic mean of all span differences during this period to assess the overall structural deformation offset characteristic value during operation. For example, the above three differences of 10 mm, 5 mm, and 15 mm are added together to obtain 30 mm, which is divided by 3 to obtain an arithmetic mean of 10 mm. This module uses this arithmetic mean as the twist pitch deviation parameter reflecting the overall fatigue deformation degree.

[0098] The fatigue early warning judgment submodule extracts the deformation deviation value based on the twist deviation parameter, compares the twist deviation parameter with the range of the preset structural failure tolerance threshold value, triggers an alarm action when the twist deviation parameter is determined to be greater than the preset structural failure tolerance threshold, summarizes the detection result data and fault point parameters and generates alarm information, and establishes a wire rope structure untwisting fatigue early warning command signal.

[0099] The fatigue early warning judgment submodule reads the deformation deviation value from the lay length deviation parameter to obtain the range of the preset structural failure tolerance threshold. The preset structural failure tolerance threshold is set at 5% of the design standard lay length span based on industry wire rope scrapping standards. Based on a 710 mm benchmark, the preset structural failure tolerance threshold is calculated to be 35.5 mm. The fatigue early warning judgment submodule compares the lay length deviation parameter with the preset structural failure tolerance threshold and performs a relational operator judgment operation. For example, if the input lay length deviation parameter is 40 mm and the preset structural failure tolerance threshold is 35.5 mm, the module determines that 40 mm is greater than 35.5 mm, meeting the alarm triggering condition. When the lay length deviation parameter is determined to be greater than the preset structural failure tolerance threshold, the fatigue early warning judgment submodule triggers a solid-state relay to close the alarm action, summarizing the detection result data and the specific longitudinal displacement fault point parameters of the abnormal section. This module packages the aggregated data with predefined alarm codes to generate fixed-format hexadecimal alarm information, outputs high-priority interrupt signals through the communication bus, and establishes a wire rope structure untwisting fatigue early warning command signal. This provides crucial underlying structural safety assessment data support for wire rope flaw detection in high-risk application scenarios such as deep well hoisting equipment, effectively preventing rope breakage accidents.

[0100] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of protection of the described technical solutions.

Claims

1. A laser diameter measuring sensor and system for wire rope flaw detection, characterized in that, This includes multiple photosensitive array receivers arranged around the perimeter of the steel wire rope, including: The boundary coordinate extraction module acquires the light intensity electrical signal value collected by the photosensitive array receiver, compares the light intensity electrical signal value with the preset light intensity reference threshold to determine the target photosensitive element position number, and outputs the photosensitive element position number as the one-dimensional coordinate value of the steel wire rope shadow boundary on the corresponding laser projection surface. The cross-section profile de-biasing module extracts the one-dimensional coordinate values ​​of the wire rope shadow boundary to construct a polygonal two-dimensional coordinate set. It then analyzes the polygonal two-dimensional coordinate set through a polygonal profile feature extraction model to extract the two-dimensional coordinates of the geometric center point that characterizes the macroscopic lateral swing state of the wire rope. Finally, it performs a translation transformation mapping on the polygonal two-dimensional coordinates to obtain a set of two-dimensional coordinate data of the true cross-section external profile of the wire rope for de-biasing. The surface defect early warning module extracts the internal coordinate points from the two-dimensional coordinate data set of the true cross-section of the deflection of the wire rope, evaluates the characteristic parameters of the difference in the radial distance between the contour coordinate points and the reference coordinate points of the wire rope, compares them with the preset surface defect tolerance threshold, and constructs an alarm electrical signal command for the surface micro-defects of the wire rope. The three-dimensional coordinate construction module extracts the radial distance extreme value feature points from the two-dimensional coordinate data set of the true cross-section of the deflection of the steel wire rope as the two-dimensional coordinates of the protrusion apex. It integrates the acquired longitudinal running speed digital signal, sampling timestamp, and the two-dimensional coordinates of the protrusion apex through the three-dimensional spiral trajectory mapping model to construct a three-dimensional coordinate set of the crest apex of the steel wire rope. The structural fatigue early warning module acquires the three-dimensional coordinate set of the peak vertices of the wire rope corresponding to adjacent time points, extracts the dynamic twist span characteristic parameters, calculates the twist deviation parameters between the twist span and the design standard, compares them with the preset structural failure tolerance threshold, and issues a wire rope structural untwisting fatigue early warning command signal.

2. The laser diameter measuring sensor and system for wire rope flaw detection according to claim 1, characterized in that: During the process of determining the target photosensitive element position number, when the light intensity electrical signal value is greater than the preset light intensity reference threshold, it is determined that the corresponding photosensitive element is in the light-receiving area; when the light intensity electrical signal value is less than or equal to the preset light intensity reference threshold, it is determined that the corresponding photosensitive element is in the occlusion area, and the photosensitive element position number corresponding to the boundary between the light-receiving area and the occlusion area is extracted.

3. The laser diameter measuring sensor and system for wire rope flaw detection according to claim 1, characterized in that: During the comparison with the preset surface defect tolerance threshold, when the cross-sectional radial distance difference characteristic parameter is greater than the preset surface defect tolerance threshold, the corresponding target coordinate point position information is extracted and the alarm electrical signal command for the small surface defect of the wire rope is constructed; when the cross-sectional radial distance difference characteristic parameter is less than or equal to the preset surface defect tolerance threshold, the cross-sectional profile of the wire rope is determined to be in good condition.

4. The laser diameter measuring sensor and system for wire rope flaw detection according to claim 1, characterized in that: During the comparison with the preset structural failure tolerance threshold, when the twist deviation parameter is greater than the preset structural failure tolerance threshold, an early warning signal for the untwisting fatigue of the wire rope structure is issued; when the twist deviation parameter is less than or equal to the preset structural failure tolerance threshold, the overall torsional state of the wire rope is determined to be safe.

5. The laser diameter measuring sensor and system for wire rope flaw detection according to claim 1, characterized in that, The boundary coordinate extraction module includes: The light intensity numerical acquisition submodule acquires the light intensity electrical signal values ​​collected by each set of photosensitive array receivers arranged around the steel wire rope during the longitudinal movement of the steel wire rope, records the changes in the peak value of the light intensity electrical signal, compares the difference between the light intensity electrical signal value and the light intensity reference threshold, extracts the deviation of the difference between the two, and generates light intensity difference amplitude feature data. The light-receiving state determination submodule, based on the light intensity difference amplitude characteristic data, determines that when the light intensity electrical signal value is greater than the preset light intensity reference threshold, the corresponding photosensitive element is in the light-receiving area, and when the light intensity electrical signal value is less than or equal to the preset light intensity reference threshold, the corresponding photosensitive element is in the occlusion area. It records and compiles all photosensitive element area distribution location information to obtain the photosensitive element light-receiving state distribution set. The boundary coordinate output submodule analyzes the jump situation between adjacent intervals of each element based on the light-receiving state distribution set of the photosensitive element, extracts the target photosensitive element position number at the boundary between the light-receiving area and the occluded area, maps the target photosensitive element position number into a linearly arranged one-dimensional coordinate value based on the projection relationship of the laser projection surface, and outputs the dynamic change of the shadow position in combination with the time dimension parameter of the sampling time, and establishes the one-dimensional coordinate value of the steel wire rope shadow boundary.

6. The laser diameter measuring sensor and system for wire rope flaw detection according to claim 1, characterized in that, The cross-sectional profile correction module includes: The contour coordinate mapping submodule obtains the corresponding one-dimensional values ​​of all receiver outputs at the same sampling time based on the one-dimensional coordinate values ​​of the steel wire rope shadow boundary, extracts the installation angle relationship of the laser transmitter, and uses the angle transformation matrix to uniformly translate and map the one-dimensional coordinate values ​​of the steel wire rope shadow boundary to the same two-dimensional rectangular coordinate system. It then compiles all coordinate points to construct the vertex set of the outer perimeter of the occlusion area and generates a polygonal two-dimensional coordinate set. The geometric center extraction submodule extracts the horizontal and vertical coordinate parameters of all vertices based on the polygon's two-dimensional coordinate set. It performs vertex summation and average calculation on all coordinate parameters to extract polygon contour feature components. It analyzes the coordinate distribution of each outer vertex of the polygon to obtain the geometric centroid parameter of the overall closed region. It assigns the horizontal and vertical components of the centroid parameter to the corresponding spatial geometric positioning point to obtain the two-dimensional coordinates of the geometric center point. The contour coordinate de-biasing module extracts the lateral deviation offset based on the two-dimensional coordinates of the geometric center point, performs a reverse translation transformation mapping operation on all vertices in the polygon two-dimensional coordinate set, deducts the lateral offset component between the geometric center and the origin from the vertex x-coordinates, eliminates the coordinate data distortion caused by the lateral swing motion trajectory of the wire rope, and establishes a set of two-dimensional coordinate data of the true external contour of the wire rope de-biasing section.

7. The laser diameter measuring sensor and system for wire rope flaw detection according to claim 1, characterized in that, The surface defect early warning module includes: The coordinate polar angle matching submodule extracts the contour coordinate points from the two-dimensional coordinate data set of the true cross-section of the deflected wire rope, establishes a two-dimensional reference coordinate set of the standard cross-section based on the calibration of the intact wire rope, performs polar angle position feature matching calculation on the contour coordinate points and the coordinate points in the two-dimensional reference coordinate set of the standard cross-section, filters and extracts the reference coordinate points with the same polar angle position, and obtains the set of polar angle matching coordinate points of the wire rope. The radial distance evaluation submodule extracts position parameters from the contour coordinate points and corresponding reference coordinate points within the set of polar angle matching coordinate points of the wire rope, calculates the straight line length between the two coordinate points according to Euclidean distance, evaluates the radial distance deviation difference between the contour coordinate points and the reference points, compiles all point-to-point distance differences and converts them into feature quantities, and obtains the cross-sectional radial distance difference feature parameters. The defect alarm generation submodule extracts numerical features based on the cross-sectional radial distance difference feature parameter, compares the cross-sectional radial distance difference feature parameter with the numerical range limit of the preset surface defect tolerance threshold, and extracts the position information of the corresponding target coordinate point when the cross-sectional radial distance difference feature parameter is greater than the surface defect tolerance threshold, and generates an electrical signal command for alarming minor defects on the surface of the wire rope.

8. The laser diameter measuring sensor and system for wire rope flaw detection according to claim 1, characterized in that, The three-dimensional coordinate construction module includes: The vertex coordinate extraction submodule analyzes the radial distribution distance characteristics of the outer contour coordinate points in the two-dimensional rectangular coordinate system region based on the two-dimensional coordinate data set of the true cross-section of the deflected wire rope. It compares the radial distances in various directions to extract the extreme radial distance feature points in the outward convex state and uses the horizontal and vertical coordinate parameters of the extreme feature points as the outer edge vertices of each strand of the wire rope to obtain the two-dimensional coordinates of the convex vertex. The longitudinal displacement integration submodule determines the relative position of the current plane in the spatial plane based on the two-dimensional coordinates of the protrusion vertex. During continuous operation sampling, it collects digital signals of longitudinal running speed representing the longitudinal running state of the wire rope and corresponding sampling timestamps. It integrates the digital signals of longitudinal running speed with the corresponding interval sampling timestamps to perform product integration to calculate the cumulative actual distance of unidirectional running and generate the absolute longitudinal displacement feature dimension. The three-dimensional coordinate splicing submodule extracts the components of the two-dimensional coordinates of the protrusion vertex and the absolute longitudinal displacement feature dimension. It takes the absolute longitudinal displacement feature dimension as the axial value of the longitudinal coordinate system in the spatial coordinate axis and performs spatial geometric dimension splicing and combination calculation with the cross-sectional horizontal and vertical values ​​represented by the two-dimensional coordinates of the protrusion vertex. It then assembles the spliced ​​vertex spatial position parameters to construct a spiral extension trajectory set and establishes a three-dimensional coordinate set of the crest vertex of the wire rope.

9. The laser diameter measuring sensor and system for wire rope flaw detection according to claim 1, characterized in that, The structural fatigue early warning module includes: The twist span extraction submodule extracts internal three-dimensional spatial points based on the three-dimensional coordinate set of the crests of the wire rope corresponding to two adjacent sampling times. It analyzes the longitudinal difference parameter of the spatial distribution span of the three-dimensional coordinate set of the crests of the wire rope in the longitudinal coordinate axis direction at two adjacent times, extracts the dynamic twist span change amount that characterizes the change state of the twist span crest spacing of the wire rope, and obtains the dynamic twist span feature parameter. The twist deviation calculation submodule extracts the dynamic span distance feature value based on the dynamic twist span feature parameter, obtains the design standard twist span benchmark set in advance according to the design index of the wire rope factory parameters, calculates the distribution of the absolute span difference between the dynamic twist span feature parameter and the design standard twist span benchmark, evaluates the overall offset feature value of structural deformation during operation, and obtains the twist deviation parameter. The fatigue early warning judgment submodule extracts the deformation deviation value based on the twist deviation parameter, compares the twist deviation parameter with the range of the preset structural failure tolerance threshold value, triggers an alarm action when the twist deviation parameter is determined to be greater than the preset structural failure tolerance threshold, summarizes the detection result data and fault point parameters and generates alarm information, and establishes a wire rope structure untwisting fatigue early warning command signal.

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