A kind of building curtain wall rebound strength testing equipment

Abstract

The invention relates to the technical field of curtain wall material detection, and in particular to a building curtain wall rebound strength detection device. Firstly, according to the ultrasonic waveform data deviation between each monitoring point and other monitoring points, a monitoring feature point with the smallest ultrasonic waveform data deviation from other monitoring points is screened out, so that the curtain wall material structure corresponding to the detection feature point can best represent the overall structural characteristics of the curtain wall material; then, the monitoring point whose corresponding ultrasonic waveform data has a high similarity with the ultrasonic waveform data of the detection feature point is used as the monitoring effective point participating in the comprehensive calculation of the rebound height, so that the comprehensive rebound height obtained by combining the height effectiveness of each monitoring effective point with the corresponding initial rebound height is more accurate, so that when the curtain wall material strength detection is performed based on the comprehensive rebound height, the influence of accidental factors is less, and the accuracy of the curtain wall material quality detection is improved.

Description

Technical Field

[0001] The invention relates to the technical field of curtain wall material detection, and in particular to a building curtain wall rebound strength detection device. Background Art

[0002] The curtain wall of a building refers to a non-load-bearing facade system, which is a building enclosure installed on the frame structure of the building without bearing structural loads. For example, the common stone curtain wall is widely used because it has good thermal insulation properties, helps maintain the temperature inside the building, improves energy efficiency, and reduces air conditioning and heating costs. However, because it needs to be installed on the outside of the building, in order to make the curtain wall have sufficient strength to withstand external forces such as wind pressure, snow loads and earthquakes, and to prevent deformation or damage, the curtain wall material needs to be tested for material strength.

[0003] The existing technology usually directly tests the strength of curtain wall materials according to the rebound height detected by the rebound strength testing equipment; however, this test can only perform strength testing on the surface of the material, while the internal structure of the existing curtain wall materials is usually more complicated and the texture is not uniform enough; when using the rebound strength testing equipment to test the strength of building curtain wall materials, the strength of different test areas is often different due to the internal texture, resulting in a greater accidental influence when the curtain wall material strength is directly tested by the rebound strength testing equipment, resulting in poor accuracy in the quality inspection of the curtain wall materials. Summary of the invention

[0004] In order to solve the technical problem that when using a rebound strength testing device to directly test the strength of building curtain wall materials in the prior art, the strength of different testing areas is often different due to internal texture reasons, resulting in a large accidental influence when the curtain wall material strength is directly tested by the rebound strength testing device, resulting in poor accuracy of the quality test of the curtain wall material, the present application provides a building curtain wall rebound strength testing device, and the technical solution adopted is as follows:

[0005] The present application provides a building curtain wall rebound strength testing device, the device comprising:

[0006] A data acquisition module, used to obtain ultrasonic waveform data of each monitoring point on the building curtain wall material and the initial rebound height of the rebound hammer;

[0007] The monitoring feature point screening module is used to determine the relative difference of the waveform of each monitoring point according to the periodic characteristic deviation between the ultrasonic waveform data of each monitoring point and the ultrasonic waveform data of other monitoring points; and screen out the monitoring feature points according to the relative difference of the waveforms of all monitoring points;

[0008] A monitoring effective point screening module is used to determine the height effectiveness of each monitoring point according to the waveform similarity between the ultrasonic waveform data of each monitoring point and the ultrasonic waveform data of the monitoring feature point; and screen out the monitoring effective points according to the height effectiveness;

[0009] The curtain wall material strength detection module is used to determine the comprehensive rebound height of the curtain wall material according to the height effectiveness of each monitoring effective point combined with the corresponding initial rebound height; and perform curtain wall material rebound strength detection according to the comprehensive rebound height.

[0010] Furthermore, the process of obtaining the relative difference of the waveform includes:

[0011] Determine the peak characteristic reference value corresponding to the ultrasonic waveform data of each monitoring point according to the average value of all peak values ​​in the ultrasonic waveform data of each monitoring point;

[0012] The ultrasonic waveform data of each monitoring point is sequentially used as target waveform data; the ultrasonic waveform data of each monitoring point other than the monitoring point corresponding to the target waveform data is used as comparison waveform data;

[0013] Determine a reference peak phase deviation of each comparison waveform data according to a time difference between a first peak of each comparison waveform data and a first peak of the target waveform data;

[0014] Determine a reference peak value deviation of each comparison waveform data according to a difference between a peak feature reference value of each comparison waveform data and a peak feature reference value of the target waveform data;

[0015] Determine a reference cycle length deviation of each comparison waveform data according to a difference between a cycle length of each comparison waveform data and a cycle length of the target waveform data;

[0016] The relative waveform difference of the target waveform data is determined according to the overall size of the reference peak phase deviation, the reference peak value deviation and the reference period length deviation of each comparison waveform data.

[0017] Furthermore, the process of determining the relative waveform difference of the target waveform data according to the overall size of the reference peak phase deviation, the reference peak value deviation and the reference cycle length deviation of each comparison waveform data includes:

[0018] Determine the comparison waveform deviation of each comparison waveform data according to the product of the reference peak phase deviation, the reference peak value deviation and the reference cycle length deviation of each comparison waveform data;

[0019] The relative difference of the waveform of the monitoring point corresponding to the target waveform data is determined according to the accumulated value of the comparison waveform deviation of all the comparison waveform data corresponding to the target waveform data.

[0020] Furthermore, the process of acquiring the monitoring feature points includes:

[0021] The monitoring point with the smallest relative waveform difference among all monitoring points is taken as the monitoring feature point.

[0022] Furthermore, the highly effective acquisition process includes:

[0023] The cosine similarity between the ultrasonic waveform data of each monitoring point and the ultrasonic waveform data of the detected feature point is taken as the height effectiveness of each monitoring point.

[0024] Furthermore, the process of acquiring the effective monitoring points includes:

[0025] The monitoring points with high effectiveness greater than the preset effectiveness threshold are regarded as effective monitoring points.

[0026] Furthermore, the process of obtaining the comprehensive rebound height includes:

[0027] Normalize the height effectiveness of each effective monitoring point to determine the rebound height weight of each effective monitoring point; determine the weighted rebound height of each effective monitoring point according to the product between the rebound height weight of each effective monitoring point and the corresponding initial rebound height;

[0028] The comprehensive rebound height of the curtain wall material is determined based on the overall size of the weighted rebound height of all effective monitoring points.

[0029] Furthermore, the process of obtaining the rebound height weight includes:

[0030] The accumulated value of the height effectiveness of all effective monitoring points is used as a reference accumulated value; and the ratio between the height effectiveness of each effective monitoring point and the reference accumulated value is used as a rebound height weight of each effective monitoring point.

[0031] Furthermore, the process of determining the comprehensive rebound height of the curtain wall material according to the overall size of the weighted rebound heights of all effective monitoring points includes:

[0032] The comprehensive rebound height of the curtain wall material is determined based on the cumulative value of the weighted rebound heights of all effective monitoring points.

[0033] Furthermore, the process of performing the rebound strength test of the curtain wall material according to the comprehensive rebound height includes:

[0034] The material strength of the curtain wall material is tested according to the comprehensive rebound height of the curtain wall material based on the rebound method.

[0035] This application has the following beneficial effects:

[0036] Considering that the curtain wall material usually has a complex internal structure and uneven texture, different rebound heights will be detected in different areas, resulting in different material strengths; therefore, if the material strength of the curtain wall material is to be analyzed as a whole, it is inevitable to analyze the rebound height of each area of ​​the curtain wall material as a whole; therefore, this application first obtains the initial rebound height of the rebound hammer at each monitoring point on the building curtain wall material. The structures corresponding to different monitoring points are usually different, resulting in different degrees of strength characterization of the curtain wall material as a whole by the initial rebound height measured at different monitoring points. Therefore, in order to determine a more accurate curtain wall material strength, this application needs to analyze the curtain wall material as a whole with a better degree of strength characterization, that is, more representative or effective monitoring points; and the ultrasonic waveform data can reflect the internal structure of the curtain wall material corresponding to each monitoring point; therefore, in order to determine a more representative or effective monitoring point, the ultrasonic waveform data of each monitoring point is collected while collecting the initial rebound height of the rebound hammer, and a more representative or effective monitoring point is screened based on the internal structure of the curtain wall material reflected by the ultrasonic waveform data.

[0037] This application uses exactly the same parameters for ultrasonic detection of different monitoring points of curtain wall materials. Therefore, if the internal structures of the detected monitoring points of the curtain wall materials are the same, the ultrasonic waveforms received by the ultrasonic probe structure should be completely consistent. However, the internal structures of curtain wall materials may have different structures, so there may be certain differences in the ultrasonic waveforms corresponding to different monitoring points. Therefore, in order to determine more representative or effective monitoring points that can reflect the internal structure of curtain wall materials, this application determines the relative difference of the waveform of each monitoring point based on the periodic characteristic deviation between the ultrasonic waveform data of each monitoring point and the ultrasonic waveform data of other monitoring points. The smaller the relative difference of the waveform, the higher the similarity of the ultrasonic waveform between the corresponding monitoring point and the overall monitoring points of the curtain wall material, that is, the more the corresponding monitoring point can characterize the overall structural characteristics of the curtain wall material, and thus further selects the most representative monitoring feature points for the overall internal structure of the curtain wall material based on the relative difference of the waveforms of each monitoring point.

[0038] In order to further reduce the influence of accidental factors on the rebound strength detection of curtain wall materials, the height effectiveness is further calculated according to the waveform similarity between the ultrasonic waveform data of each monitoring point and the ultrasonic waveform data of the monitoring feature point, so as to screen out more effective monitoring points that can represent the internal structure of the curtain wall material based on the height effectiveness, and the greater the corresponding height effectiveness, the more the area corresponding to the effective monitoring point can represent the internal structure of the curtain wall material; therefore, on the basis of the initial rebound height of each effective monitoring point, the corresponding height effectiveness is weighted to determine a more accurate comprehensive rebound height, so that the curtain wall material strength detection based on the comprehensive rebound height is less affected by accidental factors, thereby improving the accuracy of curtain wall material quality detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0040] Figure 1 A structural block diagram of a building curtain wall rebound strength detection device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0041] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of the specific implementation method, structure, characteristics and effects of a building curtain wall rebound strength detection device proposed according to the present invention, in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment, and the specific features, structures or characteristics in one or more embodiments may be combined in any suitable form. In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as implying or suggesting relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features.

[0042] Unless defined otherwise, 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 invention belongs.

[0043] The specific scheme of the building curtain wall rebound strength detection device provided by the present invention is described in detail below with reference to the accompanying drawings.

[0044] See also Figure 1, which shows a structural block diagram of a building curtain wall rebound strength detection device provided by an embodiment of the present invention, including a data acquisition module 101, a monitoring feature point screening module 102, a monitoring effective point screening module 103 and a curtain wall material strength detection module 104.

[0045] The data acquisition module 101 is used to obtain the ultrasonic waveform data of each monitoring point on the building curtain wall material and the initial rebound height of the rebound hammer.

[0046] Taking into account that the internal structure of curtain wall materials is usually complex and the texture is not uniform, different rebound heights will be detected in different areas, resulting in different detected material strengths; therefore, if the material strength of the curtain wall material is to be analyzed as a whole, it is inevitable to analyze the rebound height of each area of ​​the curtain wall material as a whole; therefore, this application first obtains the initial rebound height of the rebound hammer at each monitoring point on the building curtain wall material. However, the structures corresponding to different monitoring points are usually different, resulting in different initial rebound heights measured at different monitoring points representing different degrees of strength of the curtain wall material as a whole. Therefore, in order to determine a more accurate strength of the curtain wall material, the present application needs to analyze monitoring points that have a better degree of strength representation of the curtain wall material as a whole, that is, are more representative or effective. The ultrasonic waveform data can reflect the internal structure of the curtain wall material corresponding to the position of each monitoring point. Therefore, in order to determine more representative or effective monitoring points, the ultrasonic waveform data of each monitoring point is collected while collecting the initial rebound height of the rebound hammer, and more representative or effective monitoring points are screened based on the internal structure of the curtain wall material reflected by the ultrasonic waveform data. Therefore, the present application first needs to obtain the ultrasonic waveform data of each monitoring point on the building curtain wall material and the initial rebound height of the rebound hammer.

[0047] In a specific implementation of an embodiment of the present invention, the surface of the building curtain wall material is first gridded so that each grid is 1 cm in length and width, and the center point of each grid is used as a monitoring point, so that the monitoring points are evenly and comprehensively set on the surface of the curtain wall material. The implementer can adjust the grid size or the selection method of the monitoring point according to the specific implementation environment, which will not be further elaborated here.

[0048] In a specific implementation of an embodiment of the present invention, the process of obtaining the initial rebound height includes: for each monitoring point, first, the rebound strength detection device is perpendicular to the surface of the curtain wall material and close to the corresponding monitoring point to ensure that there is no tilt, and then the pressure button on the rebound strength detection device is pressed, so that the rebound hammer hits the surface of each monitoring point of the curtain wall material with the same force as other monitoring points, and then the rebound height data of the rebound hammer detected by the rebound strength detection device is used as the initial rebound height of the corresponding monitoring point; and then the initial rebound height of the rebound hammer corresponding to each monitoring point is collected in the same way.

[0049] In a specific implementation of an embodiment of the present invention, the process of acquiring ultrasonic waveform data includes: for each monitoring point, first, the rebound strength testing device is perpendicular to the surface of the curtain wall material and close to the corresponding monitoring point to ensure that there is no tilt, and then the ultrasonic transmission button on the rebound strength testing device is pressed to control the ultrasonic detector inside the rebound strength testing device to emit ultrasonic waves, and after the rebound strength testing device is stably perpendicular to the corresponding monitoring point position on the surface of the curtain wall material for 30 seconds, the ultrasonic waveform data of the corresponding monitoring point is collected by the ultrasonic detector; and then the ultrasonic waveform data of each monitoring point is collected in the same way.

[0050] The monitoring feature point screening module 102 is used to determine the relative waveform difference of each monitoring point according to the periodic characteristic deviation between the ultrasonic waveform data of each monitoring point and the ultrasonic waveform data of other monitoring points; and screen out the monitoring feature points according to the relative waveform differences of all monitoring points.

[0051] This application uses exactly the same parameters for ultrasonic detection of different monitoring points of curtain wall materials. Therefore, if the internal structures of the detected monitoring points of the curtain wall materials are the same, the ultrasonic waveforms received by the ultrasonic probe structure should be completely consistent. However, the internal structures of curtain wall materials may have different structures, so there may be certain differences in the ultrasonic waveforms corresponding to different monitoring points. Therefore, in order to determine more representative or effective monitoring points that can reflect the internal structure of curtain wall materials, this application determines the relative difference of the waveform of each monitoring point based on the periodic characteristic deviation between the ultrasonic waveform data of each monitoring point and the ultrasonic waveform data of other monitoring points. The smaller the relative difference of the waveform, the higher the similarity of the ultrasonic waveform between the corresponding monitoring point and the overall monitoring points of the curtain wall material, that is, the more the corresponding monitoring point can characterize the overall structural characteristics of the curtain wall material, and thus further selects the most representative monitoring feature points for the overall internal structure of the curtain wall material based on the relative difference of the waveforms of each monitoring point.

[0052] Preferably, in some possible implementations of the embodiments of the present invention, the process of acquiring the relative difference of the waveform includes:

[0053] According to the average value of all peak values ​​in the ultrasonic waveform data of each monitoring point, determine the peak characteristic reference value corresponding to the ultrasonic waveform data of each monitoring point; use the ultrasonic waveform data of each monitoring point as the target waveform data in turn; use the ultrasonic waveform data of each monitoring point other than the monitoring point corresponding to the target waveform data as the comparison waveform data. By setting the target waveform data and the comparison waveform data, the objects for difference analysis can be more clearly distinguished, and the analysis results of all ultrasonic waveform data can be determined based on the analysis results of the target waveform data. Considering that the waveform data may be affected by noise and inevitably produce certain deviations, in order to reduce the influence of noise, the present application analyzes the waveform similarity in three dimensions that are less affected by noise: phase difference, period length difference, and amplitude difference.

[0054] According to the time difference between the first peak of each comparison waveform data and the first peak of the target waveform data, the reference peak phase deviation of each comparison waveform data is determined; according to the difference between the peak characteristic reference value of each comparison waveform data and the peak characteristic reference value of the target waveform data, the reference peak value deviation of each comparison waveform data is determined; according to the difference between the cycle length of each comparison waveform data and the cycle length of the target waveform data, the reference cycle length deviation of each comparison waveform data is determined. Considering that for any two waveform data, the larger the corresponding phase difference, the larger the cycle length difference, and the larger the amplitude difference, the more dissimilar the corresponding two waveform data should be, that is, the larger the waveform difference. Therefore, when the corresponding reference peak phase deviation is larger, it means that the phase deviation between the comparison waveform data and the target waveform data is larger, and the corresponding waveform similarity is lower; and when the reference peak value deviation is larger, it means that the amplitude difference between the comparison waveform data and the target waveform data is larger, and the corresponding waveform similarity is lower; when the reference cycle length deviation is larger, it means that the cycle length deviation between the comparison waveform data and the target waveform data is larger, and the corresponding waveform similarity is lower. The target waveform data usually corresponds to multiple comparison waveform data. Therefore, the relative waveform difference of the target waveform data is further determined based on the overall size of the reference peak phase deviation, the reference peak value deviation and the reference cycle length deviation of each comparison waveform data; the smaller the relative waveform difference is, the smaller the difference between the target waveform data and each comparison waveform data is, that is, the higher the similarity between the monitoring point of the target waveform data and the internal structure corresponding to each monitoring point as a whole, the greater the effectiveness and representativeness of the corresponding monitoring point.

[0055] Preferably, in some possible implementations of the embodiments of the present invention, the process of determining the relative waveform difference of the target waveform data according to the overall size of the reference peak phase deviation, the reference peak value deviation and the reference cycle length deviation of each comparison waveform data includes:

[0056] According to the product of the reference peak phase deviation, the reference peak value deviation and the reference cycle length deviation of each comparison waveform data, the comparison waveform deviation of each comparison waveform data is determined; according to the cumulative value of the comparison waveform deviation of all comparison waveform data corresponding to the target waveform data, the relative difference of the waveform of the monitoring point corresponding to the target waveform data is determined. Since the larger the reference peak phase deviation, the larger the reference peak value deviation and the larger the reference cycle length deviation, the smaller the waveform similarity between the comparison waveform data and the target waveform data; therefore, the smaller the comparison waveform deviation, the more similar the comparison waveform data is to the target waveform data; therefore, the smaller the waveform relative difference obtained by the cumulative value of the comparison waveform deviation of all comparison waveform data corresponding to the target waveform data, the more similar the target waveform data is to all comparison waveform data as a whole, that is, the higher the similarity of the internal structure of the monitoring point corresponding to the target waveform data and the corresponding monitoring points as a whole, the greater the effectiveness and representativeness of the corresponding monitoring point; further, according to the acquisition process of the waveform relative difference of the monitoring point corresponding to the target waveform data, the waveform relative difference of all monitoring points is obtained.

[0057] In a specific implementation of the embodiment of the present invention, the process of obtaining the relative difference of the waveform is expressed by the formula: Among them, R k is the relative difference of the waveform corresponding to the kth monitoring point; N k is the number of contrast waveform data corresponding to the ultrasonic waveform data of the kth monitoring point; Δt k,i is the time difference between the first peak value of the ultrasonic waveform data of the kth monitoring point and the first peak value of the corresponding ith comparison waveform data, that is, the reference peak phase deviation of the ith comparison waveform data corresponding to the ultrasonic waveform data of the kth monitoring point; T k is the period length of the ultrasonic waveform data of the kth monitoring point; T k,i is the period length of the ith comparison waveform data corresponding to the ultrasonic waveform data of the kth monitoring point; |T k -T k,i | is the reference period length deviation of the ith comparison waveform data corresponding to the ultrasonic waveform data of the kth monitoring point; is the average value of all peak values ​​in the ultrasonic waveform data of the k-th monitoring point, that is, the peak characteristic reference value of the ultrasonic waveform data of the k-th monitoring point; is the average value of all peak values ​​in the ith comparative waveform data corresponding to the ultrasonic waveform data of the kth monitoring point, that is, the peak characteristic reference value of the ith comparative waveform data corresponding to the ultrasonic waveform data of the kth monitoring point; is the reference peak value deviation of the ith comparison waveform data corresponding to the ultrasonic waveform data of the kth monitoring point; || is the absolute value symbol.

[0058] Preferably, in some possible implementations of the embodiments of the present invention, the process of acquiring the monitoring feature points includes:

[0059] Since the smaller the relative difference of the waveform is, the greater the effectiveness and representativeness of the corresponding monitoring point is, the monitoring point with the smallest relative difference of the waveform among all monitoring points is taken as the monitoring feature point.

[0060] The effective monitoring point screening module 103 is used to determine the height effectiveness of each monitoring point according to the waveform similarity between the ultrasonic waveform data of each monitoring point and the ultrasonic waveform data of the monitoring feature point; and screen out the effective monitoring points according to the height effectiveness.

[0061] In order to further reduce the impact of accidental factors on the rebound strength detection of curtain wall materials, a high effectiveness calculation is further performed based on the waveform similarity between the ultrasonic waveform data of each monitoring point and the ultrasonic waveform data of the monitoring feature point, so as to screen out more effective monitoring points that can represent the internal structure of the curtain wall material based on the high effectiveness, so that the subsequent rebound strength detection of the curtain wall material is more accurate.

[0062] Preferably, in some possible implementations of the embodiments of the present invention, the highly effective acquisition process includes:

[0063] The cosine similarity between the ultrasonic waveform data of each monitoring point and the ultrasonic waveform data of the detection feature point is used as the height effectiveness of each monitoring point; according to the characteristics of cosine similarity, the greater the cosine similarity between the ultrasonic waveform data of the monitoring point and the ultrasonic waveform data of the detection feature point, the higher the similarity between the ultrasonic waveform data of the monitoring point and the ultrasonic waveform data of the detection feature point, that is, the more similar the internal structure of the material represented by the monitoring point is to the internal structure of the curtain wall material, that is, the more effective the rebound height measured by the corresponding monitoring point is. It should be noted that the calculation of cosine similarity between waveform data is a technical means well known to those skilled in the art, and will not be further elaborated here.

[0064] Preferably, in some possible implementations of the embodiments of the present invention, the process of acquiring the effective monitoring points includes:

[0065] Since the greater the height effectiveness, the more effective the rebound height measured by the corresponding monitoring point is, the monitoring point whose height effectiveness is greater than the preset effective threshold is further taken as the effective monitoring point. In a specific implementation of the embodiment of the present invention, the preset effective threshold is set to 0.85, and the size of the preset effective threshold can be adjusted according to the specific implementation environment, which will not be further described here.

[0066] The curtain wall material strength detection module 104 is used to determine the comprehensive rebound height of the curtain wall material according to the height effectiveness of each monitoring effective point combined with the corresponding initial rebound height; and perform the curtain wall material rebound strength detection according to the comprehensive rebound height.

[0067] Since the greater the height effectiveness of the monitoring effective point, the more the corresponding area can represent the internal structure of the curtain wall material, therefore, based on the initial rebound height of each monitoring effective point, the corresponding height effectiveness is weighted to determine a more accurate comprehensive rebound height, so that the curtain wall material strength test based on the comprehensive rebound height is less affected by accidental factors, thereby improving the accuracy of curtain wall material quality detection.

[0068] Preferably, in some possible implementations of the embodiments of the present invention, the process of obtaining the comprehensive rebound height includes:

[0069] Normalize the height effectiveness of each effective monitoring point and determine the rebound height weight of each effective monitoring point. Preferably, in some possible implementation methods of the embodiments of the present invention, the process of obtaining the rebound height weight includes: taking the cumulative value of the height effectiveness of all effective monitoring points as a reference cumulative value; taking the ratio between the height effectiveness of each effective monitoring point and the reference cumulative value as the rebound height weight of each effective monitoring point. By normalizing the height effectiveness of each effective monitoring point by using the cumulative value of the height effectiveness of all effective monitoring points as the denominator, the cumulative sum of the rebound height weights obtained by all effective monitoring points can be made 1, which is convenient for the subsequent calculation of the comprehensive rebound height. The implementer can also adopt other normalization methods according to the specific implementation environment, which will not be further elaborated here.

[0070] The weighted rebound height of each effective monitoring point is determined according to the product of the rebound height weight of each effective monitoring point and the corresponding initial rebound height; the comprehensive rebound height of the curtain wall material is determined according to the overall size of the weighted rebound heights of all effective monitoring points. Preferably, in some possible implementation methods of the embodiments of the present invention, the process of determining the comprehensive rebound height of the curtain wall material according to the overall size of the weighted rebound heights of all effective monitoring points includes: determining the comprehensive rebound height of the curtain wall material according to the cumulative value of the weighted rebound heights of all effective monitoring points. Since the cumulative sum of all rebound height weights is 1, a more accurate comprehensive rebound height is determined by accumulation based on the calculated weighted rebound heights.

[0071] In a specific implementation of the embodiment of the present invention, the process of obtaining the comprehensive rebound height is expressed by the formula: Among them, D ′ is the comprehensive rebound height of the curtain wall material; M is the number of effective monitoring points; D m is the initial rebound height of the rebound hammer at the mth effective monitoring point; S m is the height validity of the mth monitoring effective point, that is, the cosine similarity between the ultrasonic waveform data of the mth monitoring effective point and the ultrasonic waveform data of the detection feature point; S sum It is the accumulated value of the high effectiveness of all effective monitoring points; is the rebound height weight of the mth effective monitoring point; is the weighted rebound height of the mth effective monitoring point.

[0072] Preferably, in some possible implementations of the embodiments of the present invention, the process of performing a rebound strength test of the curtain wall material according to the comprehensive rebound height includes: testing the material strength of the curtain wall material according to the comprehensive rebound height of the curtain wall material based on the rebound method. It should be noted that the rebound method is a technical means well known to those skilled in the art, and the implementer can perform material strength calculation by other methods of determining the material strength according to the rebound height according to the specific implementation environment, which will not be further elaborated here.

[0073] To summarize, the present application first selects the monitoring feature points with the smallest deviation of ultrasonic waveform data from other monitoring points according to the deviation of ultrasonic waveform data between each monitoring point and other monitoring points, so that the curtain wall material structure corresponding to the detection feature point can best characterize the overall structural characteristics of the curtain wall material; and then uses the monitoring points whose corresponding ultrasonic waveform data have a high similarity with the ultrasonic waveform data of the detection feature point as the effective monitoring points participating in the comprehensive calculation of the rebound height, so that the comprehensive rebound height obtained by combining the height effectiveness of each effective monitoring point with the corresponding initial rebound height is more accurate, so that the curtain wall material strength detection based on the comprehensive rebound height is less affected by accidental factors, thereby improving the accuracy of curtain wall material quality detection.

[0074] It should be noted that the sequence of the above embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0075] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

Claims

1. A building curtain wall rebound strength testing device, characterized in that: The device comprises: A data acquisition module, used to obtain ultrasonic waveform data of each monitoring point on the building curtain wall material and the initial rebound height of the rebound hammer; The monitoring feature point screening module is used to determine the relative difference of the waveform of each monitoring point according to the periodic characteristic deviation between the ultrasonic waveform data of each monitoring point and the ultrasonic waveform data of other monitoring points; and screen out the monitoring feature points according to the relative difference of the waveforms of all monitoring points; A monitoring effective point screening module is used to determine the height effectiveness of each monitoring point according to the waveform similarity between the ultrasonic waveform data of each monitoring point and the ultrasonic waveform data of the monitoring feature point; and screen out the monitoring effective points according to the height effectiveness; The curtain wall material strength detection module is used to determine the comprehensive rebound height of the curtain wall material according to the height effectiveness of each monitoring effective point combined with the corresponding initial rebound height; and perform curtain wall material rebound strength detection according to the comprehensive rebound height.

2. A building curtain wall rebound strength testing device according to claim 1, characterized in that: The process of obtaining the relative difference of the waveform includes: Determine the peak characteristic reference value corresponding to the ultrasonic waveform data of each monitoring point according to the average value of all peak values ​​in the ultrasonic waveform data of each monitoring point; The ultrasonic waveform data of each monitoring point is sequentially used as target waveform data; the ultrasonic waveform data of each monitoring point other than the monitoring point corresponding to the target waveform data is used as comparison waveform data; Determine a reference peak phase deviation of each comparison waveform data according to a time difference between a first peak of each comparison waveform data and a first peak of the target waveform data; Determine a reference peak value deviation of each comparison waveform data according to a difference between a peak feature reference value of each comparison waveform data and a peak feature reference value of the target waveform data; Determine a reference cycle length deviation of each comparison waveform data according to a difference between a cycle length of each comparison waveform data and a cycle length of the target waveform data; The relative waveform difference of the target waveform data is determined according to the overall size of the reference peak phase deviation, the reference peak value deviation and the reference period length deviation of each comparison waveform data.

3. The building curtain wall rebound strength testing device according to claim 2, characterized in that: The process of determining the relative waveform difference of the target waveform data according to the overall size of the reference peak phase deviation, the reference peak value deviation and the reference period length deviation of each comparison waveform data includes: Determine the comparison waveform deviation of each comparison waveform data according to the product of the reference peak phase deviation, the reference peak value deviation and the reference cycle length deviation of each comparison waveform data; The relative difference of the waveform of the monitoring point corresponding to the target waveform data is determined according to the accumulated value of the comparison waveform deviation of all the comparison waveform data corresponding to the target waveform data.

4. The building curtain wall rebound strength testing device according to claim 1, characterized in that: The process of acquiring the monitoring feature points includes: The monitoring point with the smallest relative waveform difference among all monitoring points is taken as the monitoring feature point.

5. The building curtain wall rebound strength testing device according to claim 1, characterized in that: The highly effective acquisition process includes: The cosine similarity between the ultrasonic waveform data of each monitoring point and the ultrasonic waveform data of the detected feature point is taken as the height effectiveness of each monitoring point.

6. The building curtain wall rebound strength testing device according to claim 1, characterized in that: The process of obtaining the effective monitoring points includes: The monitoring points with high effectiveness greater than the preset effectiveness threshold are regarded as effective monitoring points.

7. The building curtain wall rebound strength testing device according to claim 1, characterized in that: The process of obtaining the comprehensive rebound height includes: Normalize the height effectiveness of each effective monitoring point to determine the rebound height weight of each effective monitoring point; determine the weighted rebound height of each effective monitoring point according to the product between the rebound height weight of each effective monitoring point and the corresponding initial rebound height; The comprehensive rebound height of the curtain wall material is determined based on the overall size of the weighted rebound height of all effective monitoring points.

8. The building curtain wall rebound strength testing device according to claim 7, characterized in that: The process of obtaining the rebound height weight includes: The accumulated value of the height effectiveness of all effective monitoring points is used as a reference accumulated value; and the ratio between the height effectiveness of each effective monitoring point and the reference accumulated value is used as a rebound height weight of each effective monitoring point.

9. The building curtain wall rebound strength testing device according to claim 8, characterized in that: The process of determining the comprehensive rebound height of the curtain wall material according to the overall size of the weighted rebound heights of all effective monitoring points includes: The comprehensive rebound height of the curtain wall material is determined based on the cumulative value of the weighted rebound heights of all effective monitoring points.

10. The building curtain wall rebound strength testing device according to claim 1, characterized in that: The process of performing the rebound strength test of the curtain wall material according to the comprehensive rebound height includes: The material strength of the curtain wall material is tested according to the comprehensive rebound height of the curtain wall material based on the rebound method.

Images