A flatness detection device and method for external wall insulation board

Abstract

The application relates to the technical field of flatness measurement, in particular to a flatness detection device and method for external wall thermal insulation boards. The method comprises the following steps: acquiring a measurement distance and a coordinate characteristic value; determining a fluctuation index based on the measurement distance, the fitting fluctuation of the measurement distance and the second-order fitting deviation of the coordinate characteristic value; determining a standard distance based on the measurement distance, and acquiring an anti-interference degradation index based on the difference between the measurement distance and the standard distance and the energy proportion of the wavelet basis after the fluctuation degree is changed; constructing a nonlinear compensation function based on the anti-interference degradation index to calculate a compensation amount, combining the direction of the residual error of the measurement distance to compensate and correct the measurement distance to obtain a corrected measurement distance; and detecting the flatness based on the corrected measurement distance. The application improves the detection precision of the flatness.

Description

Technical Field

[0001] This application relates to the field of flatness testing technology, specifically to a device and method for testing the flatness of external wall insulation panels. Background Technology

[0002] Exterior wall insulation boards are plate-shaped materials fixed to the outside of building exterior walls for thermal insulation. They are directly related to the performance of the building's external insulation system and have a significant impact on the quality and appearance of subsequent decoration. If the surface flatness of the exterior wall insulation board is poor, it will lead to uneven plaster layer thickness during subsequent plastering, causing risks such as hollowing and cracking. In terms of performance, it will weaken the overall thermal insulation performance of the wall. Therefore, the surface flatness test of exterior wall insulation boards is the key to ensuring their performance and function.

[0003] To ensure the smoothness and flatness of the surface of exterior wall insulation panels, existing technologies primarily use laser ranging scanning to detect their flatness. Specifically, this method uses a laser rangefinder to perform a linear scan parallel to the surface of the insulation panel. The vertical distance between the insulation panel and the rangefinder is continuously measured by the echo signal from the laser beam. The flatness of the insulation panel surface is determined by the continuous change in distance. However, existing exterior wall insulation panels are typically made of rough materials with micropores, such as polystyrene or extruded polystyrene boards. These porous and rough materials produce severe diffuse reflection and scattering when reflecting laser light, distorting the echo signal received by the laser rangefinder. This directly interferes with the accuracy of the vertical distance measurement, causing deviations in the three-dimensional coordinate data of the detection point and reducing the accuracy of the flatness detection. Summary of the Invention

[0004] To address the technical problem of decreased flatness detection accuracy caused by reflection and scattering, this application provides a flatness detection device and method for external wall insulation panels. The specific technical solution adopted is as follows:

[0005] This application proposes a device and method for detecting the flatness of external wall insulation panels, the method comprising the following steps:

[0006] At each acquisition moment, the distance from the measurement point to the external wall insulation board is collected using a laser rangefinder and recorded as the measurement distance; then, the three-dimensional coordinates of the measurement point on the insulation board are obtained, and the coordinate feature value is determined based on the coordinate distance between adjacent moments.

[0007] The distance fluctuation intensity is determined based on the fluctuation of the measured distance fitted from all acquisition times prior to each acquisition time; the overall deviation is determined based on the second-order fitting deviation of the measured distance and coordinate feature values ​​from all acquisition times prior to each acquisition time; and the fluctuation index is obtained based on the distance fluctuation intensity and the overall deviation.

[0008] The standard distance for each acquisition moment is obtained by taking the average of the measured distances at all acquisition moments prior to each acquisition moment; the degree of morphological difference is determined by the difference between the measured distances and the standard distances at all acquisition moments; the proportion of the energy of the third-layer high-frequency sub-band is obtained by using wavelet basis to obtain the fluctuation index of all acquisition moments prior to each acquisition moment as the transient fluctuation feature; the anti-interference degradation index is obtained according to the degree of morphological difference and the transient fluctuation feature.

[0009] The nonlinear compensation function is constructed based on the anti-interference degradation index to calculate the compensation amount; the residual of the measured distance at each moment is used as the compensation direction, and the measured distance is corrected by combining the compensation amount to obtain the corrected measured distance; the flatness of the external wall insulation board is detected based on the deviation between the corrected measured distance and the fitted value.

[0010] In the above scheme, this application addresses diffuse reflection caused by the porous and rough structure of the exterior wall insulation board surface. It uses sliding window analysis to determine local surface defects on the exterior wall insulation board surface and combines second-order polynomial fitting to reflect the spatiotemporal variation characteristics of the surface smoothness, thus expressing the overall unevenness of the exterior wall insulation board surface during the detection process. Then, it takes the average distance from historical acquisition times for masking and standardization, and calculates the DTW distance between the actual distance and the standard distance as the degree of overall bending deformation of the board after excluding the influence of the board's inherent planar characteristics. Combined with wavelet packet energy analysis, it expresses the actual overall defects of the exterior wall insulation board after excluding external interference. Finally, it compensates the acquired distance data in real time based on the calculated anti-interference degradation index, and determines the fitting direction through the residual of the second-order polynomial fitting. This ensures that a larger anti-interference degradation index provides greater compensation to suppress nonlinear fluctuations caused by scattering from porous materials, thereby improving the defect identification capability of laser ranging.

[0011] In one embodiment, the coordinate feature value is the Euclidean distance between the three-dimensional coordinates at each acquisition time and the three-dimensional coordinates at adjacent acquisition times.

[0012] In one embodiment, the distance fluctuation intensity is the variance of the fitting slope of all time windows after fitting the measured distances at all acquisition times before the acquisition time to different time windows.

[0013] In one embodiment, the overall deviation is the mean of the fitting residuals for all acquisition times after performing a second-order polynomial fitting on the measured distances and coordinate feature values ​​at all acquisition times prior to the acquisition time.

[0014] In one embodiment, the fluctuation index is positively correlated with both the fluctuation intensity and the degree of deviation.

[0015] In one embodiment, the degree of morphological difference is the DTW distance between the sequence of measured distances at all acquisition times and the sequence of standard distances.

[0016] In one embodiment, the anti-interference degradation index is positively correlated with transient fluctuation characteristics and the degree of morphological difference.

[0017] In one embodiment, the compensation amount is positively correlated with the anti-interference degradation index.

[0018] In one embodiment, the method of using the residual of the measured distance at each time moment as the compensation direction and combining it with the compensation amount to correct the measured distance to obtain the corrected measured distance is as follows:

[0019] , This indicates the measured distance at the current moment. This indicates that the parameters are being adjusted. This represents the compensation amount for laser ranging at the current moment. This represents the residual of the measured distance at the current moment. Represents a symbolic function. This represents an exponential function with the natural constant as its base. This indicates the corrected measured distance.

[0020] Secondly, embodiments of this application also provide a flatness detection device for external wall insulation boards, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of any of the above-described methods for detecting the flatness of external wall insulation boards.

[0021] The beneficial effects of this application are as follows:

[0022] This application addresses diffuse reflection caused by the porous and rough structure of exterior wall insulation panels. It uses sliding window analysis to determine local surface defects and combines second-order polynomial fitting to reflect the spatiotemporal variation characteristics of the panel's surface smoothness, thus providing an overall representation of the surface unevenness during the inspection process. The average distance from historical acquisition times is then demasked and standardized, and the DTW distance (actual distance vs. standard distance) is calculated as the degree of overall bending deformation of the panel after excluding the influence of the panel's inherent planar characteristics. Wavelet packet energy analysis is then used to express the actual overall defects of the exterior wall insulation panel after excluding external interference. Finally, the collected distance data is compensated in real-time based on the calculated anti-interference degradation index, and the fitting direction is determined by the residual of the second-order polynomial fitting. This ensures that a larger anti-interference degradation index provides greater compensation to suppress nonlinear fluctuations caused by scattering from porous materials, thereby improving the defect identification capability of laser ranging. Attached Figure Description

[0023] To more clearly illustrate the technical solutions and advantages in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 A flowchart of a flatness testing device for external wall insulation panels provided in one embodiment of this application;

[0025] Figure 2 This is a flowchart illustrating a method for testing the flatness of an external wall insulation board, as provided in one embodiment of this application. Detailed Implementation

[0026] To further illustrate the technical means and effects adopted by this application to achieve the intended purpose of the invention, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a device and method for detecting the flatness of exterior wall insulation panels according to this application. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0027] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0028] An embodiment of a device and method for detecting the flatness of external wall insulation panels:

[0029] The following description, in conjunction with the accompanying drawings, details the specific scheme of the flatness detection device and method for external wall insulation panels provided in this application.

[0030] like Figure 1 The diagram shows a flowchart of a flatness testing device for exterior wall insulation panels according to an embodiment of this application. The device consists of a moving unit, a measuring unit, a data acquisition unit, and a data processing unit.

[0031] The moving unit consists of a horizontally placed bracket and a motor, allowing the laser rangefinder to slide horizontally. A horizontally placed board placement platform is set below the moving unit to place the exterior wall insulation board to be tested, ensuring that it is in a horizontal reference state, so that the laser rangefinder can perform a uniform linear scan of the exterior wall insulation board to be tested.

[0032] The measurement unit consists of a laser rangefinder and a high-precision inertial measurement unit. Specifically, the high-precision inertial measurement unit is fixed on the laser rangefinder, while the laser rangefinder is mounted on the moving unit, enabling the measurement unit to accurately collect distance and position data between the external wall insulation board and the laser rangefinder.

[0033] The data acquisition unit is a data acquisition device installed on the laser rangefinder. The data acquisition device is equipped with a timestamp synchronization module to ensure that the timestamps of the two data acquisition times are aligned.

[0034] The data processing unit mainly receives and analyzes the data collected and transmitted by the data acquisition instrument, and performs algorithm analysis and processing on the collected data in subsequent steps.

[0035] Please see Figure 2 The diagram illustrates a flowchart of a method for detecting the flatness of external wall insulation panels according to an embodiment of this application. The method includes the following steps:

[0036] Step S001: Obtain the measured distance and coordinate feature values.

[0037] A laser rangefinder is used to continuously measure the distance from the external wall insulation panel to the laser rangefinder. A data acquisition device is mounted on the laser rangefinder to continuously collect the distance between the external wall insulation panel and the laser rangefinder, forming time-series data of the distance between the external wall insulation panel and the laser rangefinder. In this embodiment, the data acquisition frequency of the data acquisition device is set to 50Hz. The distance between the external wall insulation panel and the laser rangefinder at each acquisition moment is recorded as the measured distance.

[0038] A high-precision inertial measurement unit is mounted on the laser rangefinder. Using the initial acquisition time as the coordinate origin, a data acquisition device records the three-dimensional spatial coordinates of the measurement point on the external wall insulation board during each data acquisition, ensuring that the timestamps of the distance data and three-dimensional coordinate data output by the data acquisition device are synchronized. Specifically, the plane formed by the x and y axes of the three-dimensional coordinates is a horizontal plane, and the z-axis is the vertical direction. For the acquired three-dimensional coordinate data, the Euclidean distance between two adjacent acquisition times is calculated. The Euclidean distance between each acquisition time and its previous acquisition time is used as the coordinate feature value.

[0039] Thus, the measured distance and coordinate feature values ​​at each acquisition moment were obtained.

[0040] Step S002: Obtain the fluctuation index based on the fluctuation determination of the measured distance and its fitting, as well as the second-order fitting deviation of the measured distance and coordinate feature values.

[0041] The distance and coordinate feature values ​​collected at all previous acquisition times are sorted in ascending order of time to obtain the distance sequence and coordinate feature sequence.

[0042] Because exterior wall insulation boards generally use porous materials, the small pores on the surface of the porous material and the rough texture of the exterior wall insulation board will form a strong scattering medium layer. When the laser beam emitted by the laser rangefinder shines on the exterior wall insulation board, the strong scattering medium layer will produce non-directional diffuse reflection of the incident laser, reducing the intensity of the echo signal, making it impossible for the laser rangefinder to accurately capture the local undulations on the surface of the exterior wall insulation board.

[0043] Due to the strong scattering and diffuse reflection caused by the porous and rough material of the exterior wall insulation board, the measured distance obtained by the laser rangefinder will exhibit significant nonlinear fluctuations, thereby masking the distance fluctuations caused by the actual defects on the board surface. It is impossible to directly and effectively identify and quantify the true local and overall micro-undulation characteristics of the board surface from the distance sequence.

[0044] Therefore, it is necessary to fit the distance sequence. By fitting a straight line to the local window data, the change in its slope is extracted, which amplifies the abrupt signal caused by the undulation of the real surface, thereby quantifying the originally masked undulation in the noise.

[0045] Using the distance sequence at each acquisition time as input, a time window length is set, and sliding window analysis is used to perform least-squares linear fitting on the elements within each sliding window. The time-distance fitted line for all elements within each sliding window is output, and the fitting slope of the fitted line is extracted. Then, the variance of the fitting slopes for all sliding windows is calculated. The variance of the obtained fitting slope represents the fluctuation intensity of the distance change between the surface of the external wall insulation board and the laser rangefinder, i.e., the intensity of the change in the unevenness of the external wall insulation board surface. This is denoted as the distance fluctuation intensity. The larger the slope variance, the more severe the microscopic undulations on the surface of the external wall insulation board. In this embodiment, the time window length is 0.1 s.

[0046] Using the distance sequence and coordinate feature sequence at each acquisition time as input, and the timestamp and location data at each acquisition time as independent variables, and the distance data as the dependent variable, a second-order polynomial fitting algorithm is used to output the residual R of the measured distance at each acquisition time in the fitted curve. The mean of all residuals is then calculated to obtain the mean of the fitted residuals. The output mean of the fitting residuals reflects the overall deviation of the surface micro-undulations of the external wall insulation board from the ideal fitted surface between the data acquisition timestamp and the data acquisition location. This deviation is denoted as the degree of deviation. The larger the value, the greater the overall micro-undulations of the external wall insulation board surface with changes in time and space, and the worse the flatness.

[0047] The fluctuation index of the insulation board surface is obtained based on the fluctuation intensity and deviation at each acquisition time.

[0048] The fluctuation index is positively correlated with both fluctuation intensity and deviation.

[0049] It should be noted that positive correlation means that when one variable increases, the other variable also increases, and the two variables change in the same direction. When one variable changes from large to small or from small to large, the other variable also changes from large to small or from small to large. The specific relationship is determined by the actual application, and this application does not impose any special restrictions.

[0050] Preferably, in this embodiment, the expression for the fluctuation index is:

[0051] , This indicates the intensity of the distance fluctuation at the current moment. Indicates the degree of deviation at the current moment. This represents the fluctuation index at the current moment.

[0052] The fluctuation index of the surface of the external wall insulation board expresses the change of the surface smoothness of the external wall insulation board with time and space through the degree of deviation. Combined with the fluctuation intensity of the distance, it reflects the overall change of the surface smoothness of the external wall insulation board, and comprehensively reflects the overall condition of the surface unevenness of the external wall insulation board. The larger the fluctuation index, the worse the smoothness of the tested external wall insulation board surface is, and the more likely there are local or overall micro-undulations.

[0053] Thus, the fluctuation index at each moment has been obtained.

[0054] It should be noted that negative correlation means that when one variable increases, the other variable decreases accordingly. The two variables change in opposite directions. When one variable changes from large to small or from small to large, the other variable also changes from small to large or from large to small. The specific relationship can be a ratio relationship, a subtraction relationship, etc., which is determined by the actual application. This application does not impose any special restrictions.

[0055] Step S003: Determine the standard distance by measuring the distance, and obtain the anti-interference degradation index based on the difference between the measured distance and the standard distance and the energy proportion after the wavelet basis change of the fluctuation degree.

[0056] During the flatness testing of exterior wall insulation boards, the inherent characteristics of the boards (such as high reflectivity and surface coating interference) can also mask surface defects, leading to greater errors in the flatness measurement results.

[0057] For each acquisition time, the mean of all elements in the distance sequence at that acquisition time is calculated. Based on the mean calculated at all acquisition times, a standard distance sequence is constructed for each acquisition time. The length of the standard distance sequence is the same as the length of the distance sequence, and the elements in the standard distance sequence are the mean of the distances at all times before that time.

[0058] Using a distance sequence and a standard distance sequence as input, the Dynamic Time Warping (DTW) algorithm outputs the DTW distance between the distance sequence and the standard distance sequence. By setting a standard distance sequence, the inherent characteristic errors of the external wall insulation board are eliminated. The DTW algorithm is then used to quantify the degree of morphological difference between the actual tested surface and the ideal surface, and all DTW distances are recorded as the degree of morphological difference. A larger calculated DTW distance indicates a more severe degree of overall bending deformation of the board after excluding the influence of the inherent planar characteristics of the insulation board.

[0059] For each acquisition time, the fluctuation index calculated from all acquisition times prior to each acquisition time is sorted in ascending order of time to obtain the surface fluctuation sequence for each acquisition time. Then, using the surface fluctuation sequence for each acquisition time as input, the db4 wavelet basis is selected, and the wavelet packet energy analysis algorithm is used to perform a 3-level decomposition. The proportion of the energy of the high-frequency subband in the third level is output. The proportion of the energy of the high-frequency subband in the third level is the relative intensity of the energy of the high-frequency detail component in the fluctuation index of the surface of the external wall insulation board. It reflects the transient fluctuation characteristics of the micro-smoothness of the surface of the external wall insulation board. The larger the value, the more severe the micro-fluctuation of the surface morphology of the external wall insulation board and the more significant the local defects on the surface. The proportion is recorded as the transient fluctuation characteristic.

[0060] The anti-interference degradation index is obtained based on the transient fluctuation characteristics and morphological differences at each acquisition time.

[0061] The anti-interference degradation index is positively correlated with transient fluctuation characteristics and the degree of morphological difference.

[0062] Preferably, the expression for the anti-interference degradation index is:

[0063] , G represents the transient fluctuation characteristics at the current moment, and G represents the degree of morphological difference at the current moment. Represents the hyperbolic tangent function. This represents the current interference resistance degradation index.

[0064] The anti-interference degradation index of the exterior wall insulation board surface is calculated by eliminating the influence of the material characteristics of the board itself through standardized distance sequence, judging the degree of surface unevenness after eliminating the influence of the material characteristics of the board itself through dynamic time warping, and combining the intensity of surface micro-undulations analyzed by wavelet packet energy analysis. The anti-interference degradation index expresses the comprehensive defect of the surface flatness of the exterior wall insulation board. The larger the value, the worse the surface flatness of the exterior wall insulation board.

[0065] Thus, the anti-interference degradation index for each data acquisition moment was obtained.

[0066] Step S004: Calculate the compensation amount by constructing a nonlinear compensation function through the anti-interference degradation index, and then combine the direction of the residual of the measurement distance to compensate and correct the measurement distance to obtain the corrected measurement distance; detect the flatness based on the corrected measurement distance.

[0067] An error compensation model is established based on the obtained anti-interference degradation index. Specifically, a nonlinear compensation function is constructed using the anti-interference degradation index of the external wall insulation board calculated at each time step, and the compensation amount at each time step is calculated. Since a larger anti-interference degradation index indicates worse flatness, and worse flatness indicates greater scattering and refraction, resulting in greater undulation of the insulation board, the compensation amount is larger.

[0068] Therefore, the compensation amount is positively correlated with the anti-interference degradation index.

[0069] Preferably, in this embodiment, the expression of the compensation function is:

[0070] , This represents the current interference resistance degradation index. This represents the compensation amount for laser ranging at the current moment.

[0071] Due to the strong scattering interference caused by the porous material of the insulation board, the laser rangefinder will cause a directional misalignment between the measured value and the actual surface morphology. The sign of the residual implies the direction of this misalignment. When the residual at each acquisition moment is greater than 0, it indicates that the measured value is too high and needs to be compensated downward. When the residual is less than 0, the measured value is too low and needs to be compensated upward. Applying negative compensation to the overvalued value makes it smaller to restore the pit depth, and applying positive compensation to the undervalued value makes it larger to restore the protrusion height, thereby reversing the directional distortion of the measured value caused by scattering interference and ensuring that the corrected coordinates accurately reflect the true microscopic undulations of the insulation board surface.

[0072] The measurement distance at each acquisition time is adjusted based on the compensation amount. Since the compensation amount is a positive value and the compensation direction is not considered, the direction of the compensation amount is determined by combining the residual, and the measurement distance is corrected accordingly.

[0073] Preferably, in this embodiment, the corrected measurement distance is:

[0074] , This indicates the measured distance at the current moment. This indicates that the parameters are being adjusted. This represents the compensation amount for laser ranging at the current moment. This represents the residual of the measured distance at the current moment. Represents a symbolic function. This represents an exponential function with the natural constant as its base. This represents the corrected measurement distance. The adjustment parameter ranges from 0.05 to 0.1, and its purpose is to smooth the corrected measurement distance and prevent excessive deviation between the corrected and initial measurement distances. In this embodiment, the adjustment parameter is set to 0.05.

[0075] By compensating for the measurement distance in real time as described above, the nonlinear fluctuations caused by scattering from porous materials can be suppressed in the measurement coordinates. Furthermore, by using a sign function, the compensation direction can be made consistent with the actual deviation direction, thereby improving the accuracy of laser ranging and the ability to identify defects in the exterior wall insulation board. Finally, the corrected three-dimensional coordinates at each acquisition moment are obtained.

[0076] Based on the corrected 3D coordinates at all acquisition times, a 3D contour model of the exterior wall insulation board surface is reconstructed. The least squares method is used to fit the overall surface to a plane, and the deviation value between each measurement point and the fitted plane in the vertical direction is calculated. The standard deviation of all deviation values ​​is also calculated, and the standard deviation is used as a quantitative evaluation index of flatness. The smaller the standard deviation, the flatter the exterior wall insulation board surface is, and vice versa. The standard deviation of the deviation value is compared with a preset threshold. If the standard deviation is less than the preset threshold, it indicates that the flatness is good, and vice versa. In this embodiment, the preset threshold is 2.

[0077] It should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

[0078] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. A method for testing the flatness of external wall insulation panels, characterized in that, The method includes the following steps: At each acquisition moment, the distance from the measurement point to the external wall insulation board is collected using a laser rangefinder and recorded as the measurement distance; then, the three-dimensional coordinates of the measurement point on the insulation board are obtained, and the coordinate feature value is determined based on the coordinate distance between adjacent moments. The distance fluctuation intensity is determined based on the fluctuation of the measured distance fitted from all previous acquisition times; the overall deviation is determined based on the second-order fitting deviation of the measured distance and coordinate eigenvalues ​​from all previous acquisition times; the fluctuation index is obtained based on the distance fluctuation intensity and the overall deviation; the expression is: ,in, This indicates the intensity of the distance fluctuation at the current moment. Indicates the degree of deviation at the current moment. This represents the fluctuation index at the current moment; The standard distance for each acquisition moment is obtained based on the average of the measured distances at all acquisition moments prior to that moment; the degree of morphological difference is determined based on the difference between the measured distances and the standard distances at all acquisition moments; the proportion of the energy of the third-layer high-frequency subband is obtained by using a wavelet basis to obtain the fluctuation index of all acquisition moments prior to that moment as a transient fluctuation characteristic; the anti-interference degradation index is obtained based on the degree of morphological difference and the transient fluctuation characteristic; the expression is: ,in, G represents the transient fluctuation characteristics at the current moment, and G represents the degree of morphological difference at the current moment. Represents the hyperbolic tangent function. This indicates the current interference resistance degradation index; The compensation amount is calculated by constructing a nonlinear compensation function based on the anti-interference degradation index; the residual obtained by fitting the measured distance at each time step using a second-order polynomial algorithm is used as the compensation direction, and the measured distance is then corrected by combining the compensation amount to obtain the corrected measured distance. Specifically, this includes: , This indicates the measured distance at the current moment. This indicates that the parameters are being adjusted. This represents the compensation amount for laser ranging at the current moment. This represents the residual obtained using a second-order polynomial fitting algorithm, representing the measured distance at the current moment. Represents a symbolic function. This represents an exponential function with the natural constant as its base. This indicates the corrected measurement distance; the flatness of the exterior wall insulation board is detected based on the deviation between the corrected measurement distance and the fitted value.

2. The method for detecting the flatness of external wall insulation panels as described in claim 1, characterized in that, The coordinate feature value is the Euclidean distance between the three-dimensional coordinates at each acquisition time and the three-dimensional coordinates at adjacent acquisition times.

3. The method for detecting the flatness of external wall insulation panels as described in claim 1, characterized in that, The distance fluctuation intensity is the variance of the fitting slope of all time windows after fitting the measured distances at all acquisition times before the acquisition time to different time windows.

4. The method for detecting the flatness of external wall insulation panels as described in claim 1, characterized in that, The overall deviation is the mean of the fitting residuals for all acquisition times after performing a second-order polynomial fitting on the measured distances and coordinate feature values ​​at all acquisition times prior to the acquisition time.

5. The method for detecting the flatness of external wall insulation panels as described in claim 1, characterized in that, The fluctuation index is positively correlated with both fluctuation intensity and deviation.

6. The method for detecting the flatness of external wall insulation panels as described in claim 1, characterized in that, The degree of morphological difference is the DTW distance between the sequence composed of the measured distances at all acquisition times and the sequence composed of the standard distances.

7. The method for detecting the flatness of external wall insulation panels as described in claim 1, characterized in that, The anti-interference degradation index is positively correlated with transient fluctuation characteristics and the degree of morphological difference.

8. The method for detecting the flatness of external wall insulation panels as described in claim 1, characterized in that, The compensation amount is positively correlated with the anti-interference degradation index.

9. A device for detecting the flatness of exterior wall insulation panels, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the flatness detection method for external wall insulation boards as described in any one of claims 1-8.

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