Strength detection method and system of autoclaved aerated concrete block

Abstract

The application discloses a kind of strength detection method and system of autoclaved aerated concrete block, it is related to the technical field of block performance detection, the method includes steps: determining the multiple detection faces of target block and multiple detection points in the detection face;Ultrasonic detection processing is carried out to each detection point, and echo signal curve is obtained;According to the amplitude variation degree of the echo signal curve and the echo time length difference between each detection point, the comprehensive defect characteristic value of each detection point is calculated;Based on the comprehensive defect characteristic value and the defect coincidence feature between each detection point, the block defect characteristic value of each detection face is determined;According to the block defect characteristic value, the strength defect of the target block is determined.The application improves the overall block strength evaluation accuracy.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of block performance detection, and particularly relates to a strength detection method and system for autoclaved aerated concrete blocks. BACKGROUND

[0002] Autoclaved aerated concrete blocks are light-weight porous silicate products made of siliceous and calcareous materials, and have the characteristics of light weight, good thermal insulation, excellent sound insulation, strong fire resistance, good impermeability, etc., and are mainly used in interior and exterior filling walls, special function walls, low-rise buildings and non-structural components, etc.

[0003] The strength of the block is a key indicator of its quality, and is directly related to the safety and stability of the building structure. At present, the strength of the block is mainly detected by ultrasonic waves. However, in the production process of the block, the defects detected by the ultrasonic waves may appear at any position due to uneven material distribution, process fluctuations and other factors. If only a part of the positions are randomly selected for detection, and the strength of the entire block is reflected through the detection results, there will be a certain one-sidedness, so that the overall strength of the block cannot be accurately evaluated. SUMMARY

[0004] The main purpose of the present application is to provide a strength detection method and system for autoclaved aerated concrete blocks, which aims to solve the technical problem in the related art that the strength of the entire block is reflected through the detection results by randomly selecting a part of the positions for detection, which has a certain one-sidedness, so that the overall strength of the block cannot be accurately evaluated.

[0005] To achieve the above-mentioned purpose, the embodiments of the present application provide a strength detection method for autoclaved aerated concrete blocks, comprising:

[0006] determining a plurality of detection surfaces of a target block and a plurality of detection points in the detection surfaces;

[0007] performing ultrasonic detection processing on each detection point to obtain an echo signal curve;

[0008] According to the amplitude variation degree of the echo signal curve and the echo time difference between each detection point, a comprehensive defect characteristic value of each detection point is calculated;

[0009] Based on the comprehensive defect characteristic value and the defect coincidence feature between each detection point, a block defect characteristic value of each detection surface is determined;

[0010] According to the block defect characteristic value, a strength defect of the target block is determined.

[0011] In a possible implementation of the present application, the comprehensive defect characteristic value of each detection point is calculated according to the amplitude variation degree of the echo signal curve and the echo time difference between the detection points, including:

[0012] The first defect coefficient of each detection point is calculated according to the amplitude variation degree of the echo signal curve.

[0013] The comprehensive defect characteristic value of each detection point is calculated based on the first defect coefficient and the echo time difference between the detection points.

[0014] In a possible implementation of the present application, the first defect coefficient of each detection point is calculated according to the amplitude variation degree of the echo signal curve, including:

[0015] The curve peak of the echo signal curve is obtained.

[0016] The time interval between any two adjacent curve peaks is set as a waveform period to obtain a plurality of waveform periods.

[0017] The first variance of each waveform period is calculated, and the amplitude sequence of the echo signal curve is generated according to the amplitude of the curve peak.

[0018] The first-order difference of the amplitude sequence is obtained to obtain the amplitude difference sequence.

[0019] The amplitude attenuation amplitude of the detection point is obtained based on the amplitude difference between the first curve peak and the last curve peak in the echo signal curve.

[0020] The first defect coefficient of each detection point is calculated based on the first variance, the variance of the amplitude difference sequence, and the amplitude attenuation amplitude.

[0021] In a possible implementation of the present application, the comprehensive defect characteristic value of each detection point is calculated based on the first defect coefficient and the echo time difference between the detection points, including:

[0022] For any detection surface, the time difference value between the current detection point and other detection points in the current detection surface is obtained based on the time difference between the echo signals of the current detection point and the other detection points.

[0023] The comprehensive echo characteristic defect index of each detection point is calculated based on the time difference value and the time length of the waveform period sequence corresponding to the echo signal curve.

[0024] The comprehensive defect characteristic value of each detection point is calculated based on the comprehensive echo characteristic defect index and the first defect coefficient.

[0025] In one possible implementation of this application, a comprehensive echo characteristic defect index for each detection point is calculated based on the duration difference value and the duration of the waveform period sequence corresponding to the echo signal curve, including:

[0026] Determine the waveform period sequence of the echo signal curve corresponding to the current detection point, and perform a first-order difference on the waveform period sequence to obtain the waveform period difference sequence;

[0027] The sequence values ​​in the waveform periodic difference sequence that are greater than the first preset threshold are marked as waveform abrupt change periods;

[0028] Based on the duration difference value, the duration of the echo signal at the detection point, and the sum of the duration of the waveform change cycle, the comprehensive echo characteristic defect index of each detection point is obtained.

[0029] In one possible implementation of this application, the block defect characteristic value of each inspection surface is determined based on the comprehensive defect characteristic value and the defect overlap characteristics between each inspection point, including:

[0030] Mark the locations corresponding to the waveform abrupt change periods as potential defect areas;

[0031] Based on the possible defect areas, the defect similarity between each detection point is calculated;

[0032] For any given detection point, the confidence level of the potential defect region of the current detection point is obtained based on the mean of the defect similarity between the current detection point and all other detection points.

[0033] Based on the reliability of each detection point and the comprehensive defect characteristic value, the block defect characteristic value of each detection surface is determined.

[0034] In one possible implementation of this application, the defect similarity between each detection point is calculated based on possible defect regions, including:

[0035] For any inspection surface, extract the overlapping area between the current inspection point and the possible defect areas of other inspection points on the current inspection surface;

[0036] Based on the possible defect areas of the current detection point, the possible defect areas of other detection points, and the overlapping areas, the defect similarity between the current detection point and other detection points is calculated.

[0037] In one possible implementation of this application, determining the strength defect of the target block based on the block defect characteristic value includes:

[0038] The maximum value of the block defect characteristic value of each test surface is taken as the strength defect characteristic value of the entire target block;

[0039] Determine the strength defect of the target block based on the strength defect characteristic value.

[0040] In a possible implementation of the present application, the strength defect of the target block is determined based on the strength defect characteristic value, comprising:

[0041] The strength defect characteristic value is normalized to obtain a normalized characteristic value;

[0042] The normalized characteristic value is compared with a second preset threshold value;

[0043] If the comparison result shows that the normalized characteristic value is less than or equal to the second preset threshold value, it is determined that the strength of the target block meets the preset standard, otherwise, it is determined that the strength of the target block does not meet the preset standard.

[0044] To achieve the above-mentioned purpose, a strength detection system for autoclaved aerated concrete blocks is also provided, which comprises a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, the steps of the strength detection method for autoclaved aerated concrete blocks are implemented.

[0045] The present application provides a strength detection method and system for autoclaved aerated concrete blocks. In related art, a certain one-sidedness is caused by randomly selecting some positions for detection and reflecting the strength of the entire block through the detection results, so that the overall block strength cannot be accurately evaluated. In the present application, by determining a plurality of detection surfaces of the target block and a plurality of detection points in each detection surface, ultrasonic detection processing is first performed on each detection point to obtain an echo signal curve. According to the amplitude variation degree of the echo signal curve and the echo time difference between each detection point, a comprehensive defect characteristic value of each detection point is calculated. Then, according to the comprehensive defect characteristic value and the defect coincidence feature between each detection point, a block defect characteristic value of each detection surface is determined. Finally, the strength defect of the target block is calculated through the block defect characteristic value. According to the multi-dimensional analysis of the echo signals of the plurality of detection surfaces and the plurality of detection points, a comprehensive evaluation from point to surface is realized, the result misjudgment caused by missing local defects is avoided, the block defect characteristic value obtained finally can more truly reflect the actual strength of the block, and the overall block strength can be accurately evaluated. BRIEF DESCRIPTION OF DRAWINGS

[0046] Figure 1 The flowchart of the first embodiment of the strength detection method for autoclaved aerated concrete blocks of the present application;

[0047] Figure 2 The distribution diagram of the detection points involved in the strength detection method for autoclaved aerated concrete blocks of the present application;

[0048] Figure 3A comparison diagram of possible defect areas of different detection points involved in the strength detection method of autoclaved aerated concrete blocks of the application is shown in the figure.

[0049] Figure 4 A schematic diagram of the overall implementation process involved in the strength detection method of autoclaved aerated concrete blocks of the application is shown in the figure.

[0050] Figure 5 A schematic diagram of the device structure of the hardware running environment involved in the embodiment of the application is shown in the figure. DETAILED DESCRIPTION

[0051] It should be understood that the specific embodiments described herein are merely intended to explain the application and are not intended to limit the application.

[0052] The embodiment of the application provides a strength detection method of autoclaved aerated concrete blocks. Figure 1 , comprising:

[0053] Step S10, determining a plurality of detection surfaces of the target block and a plurality of detection points in the detection surfaces;

[0054] Step S20, performing ultrasonic detection processing on each detection point to obtain an echo signal curve;

[0055] Step S30, calculating a comprehensive defect characteristic value of each detection point according to the amplitude variation degree of the echo signal curve and the echo time difference between the detection points;

[0056] Step S40, determining a block defect characteristic value of each detection surface based on the comprehensive defect characteristic value and the defect coincidence feature between the detection points;

[0057] Step S50, determining a strength defect of the target block according to the block defect characteristic value.

[0058] The embodiment aims to: according to multi-dimensional analysis of echo signals of a plurality of detection surfaces and a plurality of detection points, realize comprehensive evaluation from points to surfaces, avoid the situation that the result is misjudged due to missed detection of local defects, and make the finally obtained block defect characteristic value more truly reflect the actual strength of the block, and accurately evaluate the overall block strength.

[0059] The specific steps are as follows:

[0060] Step S10, determining a plurality of detection surfaces of the target block and a plurality of detection points in the detection surfaces.

[0061] As an example, the strength detection method of autoclaved aerated concrete block can be applied to the strength detection device of autoclaved aerated concrete block, and the strength detection device of autoclaved aerated concrete block belongs to the strength detection system of autoclaved aerated concrete block, and the strength detection system of autoclaved aerated concrete block belongs to the strength detection equipment of autoclaved aerated concrete block.

[0062] As an example, the target block is an autoclaved aerated concrete block, and a plurality of detection surfaces are arranged on the autoclaved aerated concrete block, the number of detection surfaces can be 3 or 6, a plurality of detection points can be selected on each detection surface, the number of detection points can be 4 or 5, and the like, and the detection surface and the detection point can be determined by a pre-selected manner.

[0063] As an example, the determination of the detection point can be: for any one surface of the block, the center point is determined, and the center point and the four corner points are taken as the detection points, for the corner points, the edge of the block should be avoided, and the distance from the edge can be 1cm, and the distribution diagram of the selected detection points is shown in Figure 2 , wherein c1, c2, c3 and c4 are four corner points of the detection surface, and c5 is the center point of the detection surface.

[0064] As an example, the determination of the detection surface can be: the block is generally a cuboid or a cube, so when ultrasonic detection is performed, only one surface can be selected from the front, back, left, right and up and down surfaces for detection, and the selected three surfaces are adjacent, for example, the front, left and upper surfaces are taken as the detection surface.

[0065] Step S20, ultrasonic detection processing is performed on each detection point to obtain an echo signal curve.

[0066] As an example, the purpose of ultrasonic detection processing is to obtain ultrasonic signals of each detection point, and the obtained echo signals are processed to construct an echo signal curve, and the ultrasonic signal acquisition method can be: each detection point is dried and coated with a coupling agent, a suitable probe type of ultrasonic detector is selected, for example, a plane longitudinal wave probe, the probe diameter matches the structure size inside the block, the probe is placed at each detection point, and the ultrasonic signal of each detection point is collected, and the probe is perpendicular to the detection surface during detection.

[0067] As an example, the basic principle of ultrasonic signal detection is to reflect the internal structure by using the propagation characteristics of sound waves in the material. When the sound wave encounters a sound impedance difference (such as a defect interface), reflection, scattering and attenuation occur, the sound propagation path of the defect area is more complex, resulting in regular changes in the time, amplitude and other characteristics of the echo signal, which is significantly different from the uniform material. The ultrasonic echo signal detected at any detection point may be different due to differences in the internal structure or strength of different regions, for example, there are air holes or slurry precipitation, etc. For example, when the internal region corresponding to the detection point has defects, the echo signal may be longer in time and the waveform is distorted. When the internal region corresponding to the detection point has uniform material distribution and normal strength without defects, the echo signal curve will be more regular and stable. According to the distribution of the generated echo signal curve, the defects existing in the block can be detected.

[0068] In step S30, the amplitude variation degree of the echo signal curve and the echo time difference between the detection points are calculated to obtain the comprehensive defect feature value of each detection point.

[0069] As an example, the amplitude variation degree reflects the waveform change of the echo signal curve. When there is a defect, the waveform change amplitude is large, and the amplitude variation degree is also obvious. When the material in the block is uniformly distributed, the echo time difference between different detection points is small. When there is a defect, there will be chaos inside the block. At this time, the echo time difference between different detection points is large. Therefore, the amplitude variation degree and the echo time difference between the detection points can be used to determine the comprehensive defect feature value of each detection point.

[0070] As an example, the comprehensive defect feature value represents the possibility of defects at the detection point. The larger the comprehensive defect feature value, the more likely it is that there is a defect inside the detection point.

[0071] In step S30, the amplitude variation degree of the echo signal curve and the echo time difference between the detection points are calculated to obtain the comprehensive defect feature value of each detection point.

[0072] In step S31, the amplitude variation degree of the echo signal curve is calculated to obtain the first defect coefficient of each detection point.

[0073] As an example, the first defect coefficient is a defect coefficient of the detection point calculated based on the attenuation degree of the echo signal, which represents the possibility of defects at the detection point.

[0074] In step S31, the amplitude variation degree of the echo signal curve is calculated to obtain the first defect coefficient of each detection point.

[0075] a curve peak of the curve of the echo signal;

[0076] a time interval between any two adjacent curve peaks is set as a waveform period to obtain a plurality of waveform periods;

[0077] As an example, after obtaining the curve of the echo signal, the time length of the curve of the echo signal, all curve peaks, and the amplitude corresponding to each curve peak can be directly determined. The amplitude is taken as the amplitude of the curve peak. A time interval between any two adjacent curve peaks is set as a waveform period. Since there are a plurality of curve peaks, each curve peak is divided, and a plurality of waveform periods can be obtained.

[0078] a first variance of each waveform period is calculated, and an amplitude sequence of the curve of the echo signal is generated according to the amplitude of the curve peak;

[0079] a first-order difference of the amplitude sequence is obtained to obtain an amplitude difference sequence;

[0080] Specifically, the sound speed in the uniform medium is constant, and the period is only determined by the distance, so the period is stable. The defect destroys the continuity of the medium, so that the sound speed locally changes (for example, the sound speed in the hollow area tends to the sound speed in the air), which leads to the fluctuation of the period of different waveforms due to the difference in sound speed on the propagation path, and the variance increases.

[0081] As an example, the first variance is the variance value between each waveform period, denoted as The smaller the variance is, the more stable the period of all waveforms in the signal is, and the more likely the material inside the block at the detection point is uniform and defect-free.

[0082] As an example, the amplitude of each curve peak is integrated to obtain an amplitude sequence of the curve of the echo signal. Then, a first-order difference of the amplitude sequence is obtained to obtain a corresponding amplitude difference sequence. The amplitude difference sequence is a first-order difference sequence, and the first-order difference is a prior art, which will not be described in detail here. When the value in the first-order difference sequence is negative, it indicates that the amplitude is attenuated. The more consistent the values in the first-order difference sequence are, the more constant the attenuation amplitude of the amplitude is, and the more likely it is a defect-free region.

[0083] Specifically, the uniformity of the defect-free region is high, the sound wave propagation path is stable, and the energy loss is mainly from the absorption of the material itself (the attenuation rate is relatively constant), so the amplitude attenuation presents regularity, the values in the first-order difference sequence tend to be consistent, and the defect (such as a pore or a crack) will cause a sudden change in acoustic impedance, causing a sudden loss of energy, making the amplitude attenuation rate fluctuate, and the difference between the values in the difference sequence increases.

[0084] Based on the amplitude difference between the first curve peak and the last curve peak in the curve of the echo signal, an amplitude attenuation amplitude of the detection point is obtained;

[0085] As an example, the defects (such as pores, cavities, cracks, etc.) in the block change the propagation path of the sound wave, increase the energy loss, and cause the amplitude attenuation of the echo signal curve to increase. Specifically, the defects such as pores, cavities, and cracks change the propagation path of the sound wave, causing scattering, reflection, and diffraction, instead of straight-line propagation, increasing the propagation distance and energy loss. At the same time, the defect interface has a large acoustic impedance difference, and the energy loss is large when the sound wave is reflected and transmitted. The medium in the defect also increases the energy loss. These factors together cause the energy received by the echo signal to decrease, which is manifested as an increase in the amplitude attenuation of the echo signal curve.

[0086] As an example, the amplitude difference between the first curve peak and the last curve peak in the echo signal curve is calculated, and the amplitude difference is taken as the amplitude attenuation amplitude of the signal, denoted by b. The greater the value of b, the more the amplitude attenuation.

[0087] Based on the first variance, the variance of the amplitude difference sequence, and the amplitude attenuation amplitude, the first defect coefficient of each detection point is calculated.

[0088] As an example, the calculation method of the first defect coefficient A can be:

[0089]

[0090] wherein, represents the first variance, represents the variance of the amplitude difference sequence, The greater the value of b, the more unstable the amplitude attenuation amplitude; b represents the amplitude attenuation amplitude, represents the abnormal characteristics of the amplitude attenuation. The greater the variance of the amplitude difference sequence and the greater the overall attenuation amplitude, the more abnormal the amplitude attenuation, the more abnormal the amplitude attenuation, and the more unstable the waveform period, the more unstable the echo signal, and the more likely the block has a strength defect at the detection point.

[0091] Similarly, the first defect coefficient of other detection points can also be obtained.

[0092] Step S32, based on the first defect coefficient and the echo time difference between each detection point, the comprehensive defect characteristic value of each detection point is calculated.

[0093] As an example, after the first defect coefficient is calculated, the defect distribution at each detection point is comprehensively determined by combining the first defect coefficient and the echo time difference between each detection point, and then the comprehensive defect characteristic value is obtained, improving the accuracy of defect determination.

[0094] The step S32 of calculating the comprehensive defect characteristic value of each detection point based on the first defect coefficient and the echo duration difference between the detection points comprises:

[0095] For any detection surface, the duration difference value between the current detection point and other detection points in the current detection surface is obtained based on the duration difference between the echo signals of the current detection point and other detection points in the current detection surface.

[0096] As an example, in the production process of the block, the material strength and defect distribution in the detection surface will have spatial differences due to the influence of factors such as mixing uniformity and molding pressure. For example, insufficient mixing will cause the cement paste and aggregate to separate, resulting in local strength differences. Uneven vibration process will cause air holes or cavities to concentrate in the corner area. Therefore, the possible defect coefficients of the block represented by different detection points in the same detection surface of the block may have certain differences, so it is necessary to compare the echo signal curves of different detection points in the same detection surface to reflect the defect degree of the block through the echo signal of each detection point.

[0097] Since the block is a regular cube or cuboid, the distance between any two opposite detection points on the two opposite surfaces is the same. Therefore, if the material in the block is uniform, the duration of the echo signal of each detection point should also be the same. If the duration of a certain echo signal is longer than that of the others, it indicates that there may be defects such as air holes and cavities in the internal area of the detection point that affect the strength. The defect area has a significantly lower sound speed than dense materials, resulting in an extended propagation time.

[0098] As an example, when comparing the echo durations between the detection points, the detection points in the same detection surface are compared, and then the duration difference values between the detection points in multiple detection surfaces are obtained. The duration difference value is based on the absolute value of the duration difference between the echo signals of the current detection point and other detection points in the current detection surface, and is obtained by averaging. It is used to represent the difference in echo duration between the current detection point and other detection points. The greater the value of a, the greater the difference in echo duration with other detection points, and the more likely it is that there are defects affecting the strength of the block at this detection point. The smaller the value of a, the more consistent the echo duration with other detection points, and the less the defect affects the echo duration.

[0099] Based on the duration difference value and the duration of the waveform period sequence corresponding to the echo signal curve, the comprehensive echo characteristic defect index of each detection point is calculated.

[0100] As an example, the length difference value between each detection point and the length of the waveform period sequence corresponding to the echo signal curve are calculated, and the comprehensive echo feature defect index of each detection point is calculated based on the length difference value and the length of the waveform period sequence corresponding to the echo signal curve, which is based on the length difference of the detection point to determine whether there is a defect at the detection point.

[0101] The step of calculating the comprehensive echo feature defect index of each detection point based on the length difference value and the length of the waveform period sequence corresponding to the echo signal curve comprises:

[0102] The waveform period sequence corresponding to the echo signal curve of the current detection point is determined, and the waveform period sequence is first differentiated to obtain a waveform period difference sequence.

[0103] As an example, the waveform period has been determined above, and the waveform period sequence can be obtained by integrating each waveform period in the echo signal curve, and the waveform period difference sequence is obtained by first differentiating the waveform period sequence.

[0104] The sequence value in the waveform period difference sequence that is greater than the first preset threshold is marked as a waveform mutation period.

[0105] As an example, the first preset threshold can be 0.5, 0.6, etc., and is not limited in particular.

[0106] As an example, taking 0.5 as the first preset threshold, when the sequence value in the waveform period difference sequence is greater than 0.5, it is considered that the period change amplitude at this point is large, which may be caused by a defect, and it is recorded as a waveform mutation period; when the sequence value in the first difference sequence is less than or equal to 0.5, it is considered that the period change amplitude at this point is small, which is within the normal fluctuation range of the period, and it is recorded as a normal period.

[0107] Based on the length difference value, the echo signal length of the detection point, and the length sum of the waveform mutation periods, the comprehensive echo feature defect index of each detection point is obtained.

[0108] As an example, the calculation method of the comprehensive echo feature defect index D of each detection point can be:

[0109]

[0110] Wherein, t represents the length sum of all waveform mutation periods; t0 represents the echo signal length of the detection point, The greater the value, the more mutation periods there are in the echo signal, and the more defects there are; a represents the length difference value, the greater the value of a, the more likely there is a defect at the detection point, and the greater the comprehensive echo feature defect index.

[0111] Based on the comprehensive echo characteristic defect index and the first defect coefficient, the comprehensive defect characteristic value of each detection point is calculated.

[0112] As an example, the calculation method of the comprehensive defect characteristic value E can be:

[0113]

[0114] Wherein, A represents the first defect coefficient of the block of the region reflected by the echo signal curve of each detection point; The comprehensive echo characteristic defect index indicates that the larger the comprehensive echo characteristic defect index is, the more likely the detection point has defects, and the larger the comprehensive defect characteristic value of the detection point is.

[0115] Step S40, based on the comprehensive defect characteristic value and the defect coincidence characteristic between each detection point, the block defect characteristic value of each detection surface is determined.

[0116] As an example, the comprehensive defect characteristic value of each detection point in the detection surface is determined, and the defect characteristic values of different detection points in the same detection surface are not completely the same. The block defect reflected by each detection surface needs to be determined comprehensively according to the defect coincidence characteristic between different detection points, so as to further determine the defect of the whole block.

[0117] As an example, the block defect characteristic value is used to represent the intensity defect of each detection surface. The larger the block defect characteristic value is, the more defects the current detection surface has.

[0118] Wherein, the step S40 of determining the block defect characteristic value of each detection surface based on the comprehensive defect characteristic value and the defect coincidence characteristic between each detection point comprises:

[0119] The position corresponding to the waveform mutation period is marked as a possible defect region;

[0120] Based on the possible defect region, the defect similarity between each detection point is calculated;

[0121] As an example, after determining the waveform mutation period, the position of the waveform mutation period is taken as the possible defect region inside the block region where the current detection point is located. Similarly, the possible defect region in the echo signal of other detection points in the same detection surface can be determined.

[0122] As an example, for each detection point, there is at least one possible defect region. The defect similarity between each detection point can be calculated according to the coincidence degree of the possible defect regions between different detection points. The defect similarity is used to represent the similarity degree of the defects existing in two detection points, such as the similarity degree of the defect distribution position, the similarity degree of the defect shape, etc.

[0123] The step of calculating the defect similarity between each detection point based on the possible defect area includes:

[0124] For any detection surface, the overlapping area between the possible defect area of the current detection point and the possible defect area of other detection points in the current detection surface is extracted.

[0125] As an example, different detection surfaces are analyzed respectively, and in the same detection surface, the overlapping area between the possible defect area of the current detection point c1 and the possible defect area of all other detection points, that is, the overlapping length of all waveform mutation periods, is obtained, denoted as f.

[0126] The comparison diagram of the possible defect areas of different detection points is shown in Figure 3 , wherein, Figure 3 C1 and C2 in represent two detection points for comparison, wherein the line segment at serial number 3 / 4 / 5 / 7 / 8 of C1 represents the waveform mutation period of C1, and the line segment at serial number 2 / 4 / 5 / 6 of C2 represents the waveform mutation period of C2; the area between the dashed lines between serial number 2 and serial number 3, the area corresponding to serial number 4 and serial number 5, and the dashed line area containing serial number 7 of C1 and serial number 6 of C2 all represent the overlapping area of the waveform mutation periods of the two detection points.

[0127] Based on the possible defect area of the current detection point, the possible defect area of other detection points, and the overlapping area, the defect similarity between the current detection point and other detection points is calculated.

[0128] As an example, taking detection point c1 and detection point c2 as an example, the calculation method of defect similarity C can be:

[0129]

[0130] Wherein, f1 represents the possible defect area of detection point c1; f represents the overlapping area of the possible defects; f2 represents the possible defect area of detection point c2; the larger the proportion of f in f1, the higher the coincidence rate of the possible defect areas of c1 and c2, and both of them may have defects at the same height, and the larger the proportion of f in f2, the more similar the defect areas of c1 and c2.

[0131] Similarly, the defect similarity between the current detection point and other detection points can be calculated.

[0132] For any detection point, based on the average value of the defect similarity between the current detection point and all other detection points, the credibility of the possible defect area of the current detection point is obtained.

[0133] As an example, in the same detection surface, the average of the similarity of each detection point to the possible defect area of other detection points is taken as the credibility of the possible defect area of the current detection point, denoted as C0. The greater the value of C0, the more defects exist in the same place as other detection points, and the more credible the waveform mutation period of the possible defect is.

[0134] Based on the credibility of each detection point and the comprehensive defect feature value, the block defect feature value of each detection surface is determined.

[0135] As an example, after calculating the credibility of each detection point, the block defect feature value of the entire detection surface is determined in combination with the comprehensive defect feature value.

[0136] As an example, the calculation method of the block defect feature value F can be:

[0137]

[0138] wherein, denotes the comprehensive defect feature value of the i-th detection point, denotes the credibility of the i-th detection point, wherein the number of detection points set in the formula is 5, and can also be other values, and is not limited in particular. C0 is taken as the weight of the comprehensive defect feature value of each detection point, and the block defect feature value of the entire detection surface is calculated, and then the block defect feature value of each detection surface is obtained.

[0139] Step S50, determining the strength defect of the target block according to the block defect feature value.

[0140] As an example, the strength defect of the entire target block is determined according to the block defect feature value of each detection surface.

[0141] wherein, the step S50 of determining the strength defect of the target block according to the block defect feature value comprises:

[0142] Step S51, taking the maximum value of the block defect feature value of each detection surface as the strength defect feature value of the entire target block.

[0143] As an example, in order to consider the comprehensiveness of the possible defects of the block at different positions reflected by different detection surfaces, based on the "most unfavorable principle" of engineering safety, the maximum value of the block defect feature value of all detection surfaces is taken as the strength defect feature value G of the autoclaved aerated concrete block, so as to capture the dominant influence of the most serious defect on the strength of the block, and ensure the conservatism and reliability of the strength defect detection.

[0144] Step S52, determining the strength defect of the target block based on the strength defect feature value.

[0145] As an example, according to the strength defect characteristic value of the whole block, the strength defect characteristic value is compared with a standard value, and the existing strength defect of the target block is determined according to the comparison result, so as to carry out subsequent processing.

[0146] The step S52 of determining the strength defect of the target block based on the strength defect characteristic value includes:

[0147] The strength defect characteristic value is normalized to obtain a normalized characteristic value.

[0148] The normalized characteristic value is compared with a second preset threshold.

[0149] As an example, the normalized processing mode can be to normalize the strength defect characteristic value by a Sigmoid function, to normalize the strength defect characteristic value G of the whole block to the range of (0, 1) to obtain the normalized characteristic value, so as to facilitate subsequent comparison.

[0150] As an example, the second preset threshold can be 0.6, 0.7, etc., and is not limited specifically.

[0151] If the comparison result shows that the normalized characteristic value is less than or equal to the second preset threshold, it is determined that the strength of the target block meets the preset standard, otherwise, it is determined that the strength of the target block does not meet the preset standard.

[0152] As an example, the greater the strength defect characteristic value, the more defects exist in the target block, and the greater the normalized characteristic value in the comparison, the more defects exist in the target block. Taking the second preset threshold of 0.7 as an example, when the normalized value is less than or equal to 0.7, it is considered that the strength of the block is normal and meets the preset standard, and can be normally applied to various scenes; when the normalized value is greater than 0.7, it is considered that the strength of the block is poor and does not meet the preset standard, and should be checked or scrapped.

[0153] Specifically, the whole implementation process of the embodiment of the present application is shown in the flowchart as Figure 4 First, the related data of each detection point in the target block is collected, and the comprehensive echo defect index of each detection point is calculated, then the block defect characteristic value of each detection surface and the strength defect characteristic value of the whole block are determined, so as to complete the strength detection of the whole block.

[0154] The application provides a strength detection method of autoclaved aerated concrete blocks. In the related art, part of positions are randomly selected for detection, and the strength of the entire block is reflected through the detection result, which has certain one-sidedness, so that the overall block strength cannot be accurately evaluated. In the application, a plurality of detection surfaces of a target block and a plurality of detection points in each detection surface are determined, ultrasonic detection processing is first performed on each detection point to obtain an echo signal curve, a comprehensive defect characteristic value of each detection point is calculated according to the amplitude change degree of the echo signal curve and the echo time difference between the detection points, then the block defect characteristic value of each detection surface is determined according to the comprehensive defect characteristic value and the defect coincidence feature between the detection points, and finally the strength defect of the target block is calculated through the block defect characteristic value. According to the multi-dimensional analysis of the echo signals of the plurality of detection surfaces and the plurality of detection points, comprehensive evaluation from points to surfaces is realized, the result misjudgment caused by the missed detection of local defects is avoided, the block defect characteristic value obtained finally can more truly reflect the actual strength of the block, and the overall block strength can be accurately evaluated.

[0155] Specifically, the application also provides a strength detection system of autoclaved aerated concrete blocks, which comprises a memory, a processor, and a computer program stored in the memory and running on the processor, and the processor implements the steps of the strength detection method of autoclaved aerated concrete blocks when executing the computer program.

[0156] Reference Figure 5 , Figure 5 is a device structure schematic diagram of a hardware running environment involved in the application embodiment scheme.

[0157] As Figure 5 shown, the strength detection device of autoclaved aerated concrete blocks can comprise a processor 1001, a memory 1005, and a communication bus 1002. The communication bus 1002 is used to realize the connection communication between the processor 1001 and the memory 1005.

[0158] Optionally, the strength detection device of autoclaved aerated concrete blocks can further comprise a user interface, a network interface, a camera, an RF (Radio Frequency, radio frequency) circuit, a sensor, a WiFi module and the like. The user interface can comprise a display screen (Display), an input sub-module such as a keyboard (Keyboard), and the optional user interface can further comprise a standard wired interface and a wireless interface. The network interface can comprise a standard wired interface and a wireless interface (such as a WI-FI interface).

[0159] Those skilled in the art can understand, Figure 5The strength detection device structure of autoclaved aerated concrete blocks shown in the figures does not constitute a limitation on the strength detection device of autoclaved aerated concrete blocks, and can include more or fewer components than shown, or combine certain components, or different component arrangements.

[0160] As shown in Figure 5 The memory 1005 as a storage medium can include an operating system, a network communication module, and a strength detection program of autoclaved aerated concrete blocks. The operating system is a program that manages and controls the hardware and software resources of the strength detection device of autoclaved aerated concrete blocks, supports the running of the strength detection program of autoclaved aerated concrete blocks and other software and / or programs. The network communication module is used to realize the communication between the components inside the memory 1005, and the communication with other hardware and software in the strength detection system of autoclaved aerated concrete blocks.

[0161] In the strength detection device of autoclaved aerated concrete blocks shown in Figure 5 The processor 1001 is used to execute the strength detection program of autoclaved aerated concrete blocks stored in the memory 1005, and realize the steps of any one of the strength detection methods of autoclaved aerated concrete blocks described above.

[0162] The specific implementation of the strength detection device of autoclaved aerated concrete blocks in this application is basically the same as that of the above-mentioned strength detection method of autoclaved aerated concrete blocks, and will not be repeated here.

[0163] It should be noted that in this paper, the term "includes", "contains" or any other variant thereof is intended to cover non-exclusive inclusion, so that the process, method, article or system including a series of elements not only includes those elements, but also includes other elements not explicitly listed, or includes elements inherent to such process, method, article or system. Without more limitations, the element defined by the statement "includes a" does not exclude the presence of another identical element in the process, method, article or system including the element.

[0164] The above-mentioned serial numbers of the embodiments of the application are only for description, and do not represent the advantages and disadvantages of the embodiments.

[0165] Those skilled in the art can clearly understand the above-mentioned embodiment method can be realized by means of software and the necessary general hardware platform, of course, it can also be realized by hardware, but in many cases, the former is a better embodiment. Based on such understanding, the technical solutions of the present application can be embodied in the form of a software product, which is stored in a storage medium (such as a ROM / RAM, a magnetic disk, or an optical disc) and includes a number of instructions for causing a terminal device (which can be a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the methods of various embodiments of the present application.

[0166] The above are only preferred embodiments of the present application, and do not limit the scope of the application. Any equivalent structure or equivalent process transformation, or direct or indirect application in other related technical fields, is also included in the scope of protection of the present application.

[0167] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description, and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multi-task processing and parallel processing are possible or can be advantageous.

[0168] Each embodiment in the specification is described in a progressive manner, and the same or similar parts between each embodiment can be referred to each other. Each embodiment focuses on the difference from other embodiments.

Claims

1. A method for detecting the strength of autoclaved aerated concrete blocks, characterized by, The method comprises: determining a plurality of detection surfaces of a target block and a plurality of detection points in the detection surfaces; performing ultrasonic detection processing on each of the detection points to obtain an echo signal curve; calculating a comprehensive defect characteristic value of each of the detection points according to a variation degree of an amplitude of the echo signal curve and a difference in echo time length between the detection points; the calculating a comprehensive defect characteristic value of each of the detection points according to a variation degree of an amplitude of the echo signal curve and a difference in echo time length between the detection points comprises: calculating a first defect coefficient of each of the detection points according to the variation degree of the amplitude of the echo signal curve; the calculating a first defect coefficient of each of the detection points according to the variation degree of the amplitude of the echo signal curve comprises: obtaining a curve peak of the echo signal curve; setting a time interval between any two adjacent curve peaks as a waveform period to obtain a plurality of waveform periods; calculating a first variance of each of the waveform periods, and generating an amplitude sequence of the echo signal curve according to the amplitudes of the curve peaks; performing first-order difference on the amplitude sequence to obtain an amplitude difference sequence; obtaining an amplitude attenuation amplitude of the detection point based on a difference in amplitude between a first curve peak and a last curve peak in the echo signal curve; calculating a first defect coefficient of each of the detection points based on the first variance, a variance of the amplitude difference sequence, and the amplitude attenuation amplitude; calculating a comprehensive defect characteristic value of each of the detection points based on the first defect coefficient and the difference in echo time length between the detection points; the calculating a comprehensive defect characteristic value of each of the detection points based on the first defect coefficient and the difference in echo time length between the detection points comprises: for any detection surface, obtaining a time length difference value between a current detection point and other detection points in the current detection surface based on a time length difference between echo signals of the current detection point and the other detection points; calculating a comprehensive echo feature defect index of each detection point based on the time length difference value and a time length of a waveform period sequence corresponding to the echo signal curve; the calculating a comprehensive echo feature defect index of each detection point based on the time length difference value and a time length of a waveform period sequence corresponding to the echo signal curve comprises: determining a waveform period sequence of the echo signal curve corresponding to the current detection point, and performing first-order difference on the waveform period sequence to obtain a waveform period difference sequence; marking a sequence value greater than a first preset threshold in the waveform period difference sequence as a waveform mutation period; obtaining a comprehensive echo feature defect index of each detection point based on a sum of the time length difference value, an echo signal time length of the detection point, and a time length of the waveform mutation period; calculating a comprehensive defect characteristic value of each of the detection points based on the comprehensive echo feature defect index and the first defect coefficient; determining a block defect characteristic value of each of the detection surfaces based on the comprehensive defect characteristic value and a defect coincidence feature between the detection points; The brick defect feature value of each detection surface is determined based on the comprehensive defect feature value and the defect coincidence feature between each detection point, and the method comprises the following steps: Marking the position corresponding to the waveform mutation period as a possible defect area; Based on the possible defect area, the defect similarity between each detection point is calculated; The defect similarity between each detection point is calculated based on the possible defect area, and the method comprises the following steps: For any detection surface, the overlapping area between the possible defect area of the current detection point and the possible defect area of other detection points in the current detection surface is extracted; Based on the possible defect area of the current detection point, the possible defect area of other detection points and the overlapping area, the defect similarity between the current detection point and other detection points is calculated; For any detection point, the credibility of the possible defect area of the current detection point is obtained based on the average value of the defect similarity between the current detection point and all other detection points; Based on the credibility of each detection point and the comprehensive defect feature value, the brick defect feature value of each detection surface is determined; The strength defect of the target brick is determined according to the brick defect feature value.

2. The method of claim 1, wherein the autoclaved aerated concrete block has a strength of 5 to 15 MPa. The strength defect of the target brick is determined according to the brick defect feature value, and the method comprises the following steps: The maximum value of the brick defect feature value of each detection surface is taken as the strength defect feature value of the entire target brick; The strength defect of the target brick is determined based on the strength defect feature value.

3. The method of claim 2, wherein the autoclaved aerated concrete block has a strength of 5.0 MPa or more. The strength defect of the target brick is determined based on the strength defect feature value, and the method comprises the following steps: The strength defect feature value is normalized to obtain a normalized feature value; The normalized feature value is compared with a second preset threshold value; If the comparison result shows that the normalized feature value is less than or equal to the second preset threshold value, it is determined that the strength of the target brick meets the preset standard, otherwise, it is determined that the strength of the target brick does not meet the preset standard.

4. A system for detecting the strength of an autoclaved aerated concrete block, characterized by, The system comprises a memory, a processor and a computer program stored in the memory and running on the processor, and when the processor executes the computer program, the steps of the method of any one of claims 1-3 are implemented.

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