Quality detection method and system for tiles

Abstract

The invention discloses a quality detection method and system for tiles, and relates to the technical field of tile quality detection.The method comprises the steps that laser is emitted to the surface of a red tile to scan the surface of the tile, and whether the surface of the red tile has a quality problem or not is judged; when no quality problem exists on the surface of the red tile, whether the quality problem exists in the red tile or not is further judged by emitting ultrasonic waves to the red tile, and compared with the mode of detecting whether the quality problem exists in the red tile or not through images, the mode of detecting whether the quality problem exists in the red tile or not through images is more accurate. The detail information of the surfaces of the tiles can be accurately obtained through laser scanning, and the influence of factors such as illumination, angles and surface reflection in traditional image detection is avoided; the ultrasonic technology can go deep into the tile to detect potential defects under the surface, such as cracks and holes; the combination of laser and ultrasonic waves enables the tile quality detection process to be more comprehensive, thereby improving the accuracy and reliability of the whole detection.

Description

Technical Field

[0001] The present invention relates to the technical field of brick and tile quality inspection, and particularly relates to a quality inspection method and system for bricks and tiles. Background Art

[0002] The quality inspection of red bricks and tiles mainly involves multiple aspects such as appearance quality, physical properties, mechanical properties, and durability performance to ensure that they meet the usage requirements of construction projects. Among them, the defect detection of bricks and tiles is an important link in quality assessment; the appearance quality inspection mainly checks whether the shape of the bricks and tiles is regular, whether the dimensions meet the standards, and whether there are defects such as cracks, missing corners, and warping on the surface; the internal defect detection focuses on factors such as pores, fissures, and inclusions that may affect the strength and durability of bricks and tiles; in addition, the physical property detection includes measuring the water absorption rate, density, and porosity to evaluate the impermeability and durability of bricks and tiles, and the compressive strength and flexural strength of bricks and tiles are realized by applying loads with a press to measure their bearing capacity; it also includes the durability performance detection of red bricks and tiles, involving frost resistance, weather resistance, acid and alkali resistance, and fire resistance detection. Usually, freeze-thaw cycle experiments, aging experiments, chemical erosion experiments, and firing experiments at different temperatures are used to evaluate the stability and service life of bricks and tiles in different environments. Through these comprehensive detection means, the quality of red bricks and tiles can be comprehensively judged to ensure their safety and reliability in construction projects.

[0003] Among them, the defect detection of bricks and tiles is an important link in quality assessment. The existing method is to obtain the image of the brick and tile surface and analyze the image to judge whether there are defects in the bricks and tiles and whether they meet the standards; however, image detection mainly relies on surface features and it is difficult to detect hidden defects such as internal cracks, pores, or inclusions in bricks and tiles, resulting in incomplete detection; affected by factors such as light, shooting angle, and surface reflection, the image quality may be deviated, reducing the accuracy of detection; in addition, if there are color changes or complex textures on the brick and tile surface, it may interfere with the algorithm judgment, resulting in misdetection or missed detection; therefore, it is difficult to achieve high-precision and comprehensive brick and tile defect detection only relying on image analysis. Summary of the Invention

[0004] The object of the present invention is to solve the above-mentioned problems and provide a quality inspection method and system for bricks and tiles.

[0005] In the first aspect of the implementation of the present invention, a quality inspection method for bricks and tiles is first proposed. The method includes:

[0006] Emitting laser to scan the surface of red bricks and tiles and calculating the reflection intensity non-uniformity coefficient according to the strength of the reflected signal; evaluating whether the distribution of the reflected signal on the brick and tile surface is uniform;

[0007] Obtain the phase of the reflected signal, and calculate the phase anomaly change coefficient based on the phase of the reflected signal; evaluate the abnormal fluctuation of the phase of the reflected signal on the surface of the brick and tile;

[0008] Obtain the surface quality defect coefficient based on the reflection intensity non-uniformity coefficient and the phase anomaly change coefficient, and judge whether there are quality problems on the surface of the red brick and tile according to the surface quality defect coefficient.

[0009] Optionally, the calculation steps of the reflection intensity non-uniformity coefficient and the phase anomaly change coefficient are as follows:

[0010] Emit laser light to the surface of the brick and tile, receive the reflected signal, and extract the reflection intensity values at the corresponding positions according to different positions in the scanned area;

[0011] Calculate the mean and standard deviation of all the reflection intensity values, and divide the standard deviation by the mean to obtain the reflection intensity non-uniformity coefficient;

[0012] Emit laser light to the surface of the brick and tile, receive the reflected signal; extract the phase values of the reflected signals at the corresponding positions according to different positions in the scanned area;

[0013] Calculate the mean of the phase values of all the reflected signals, calculate the absolute difference between the phase value of each reflected signal and the mean, and calculate the sum of all the absolute differences to obtain the phase anomaly change coefficient.

[0014] Optionally, the steps of obtaining the surface quality defect coefficient based on the reflection intensity non-uniformity coefficient and the phase anomaly change coefficient, and judging whether there are quality problems on the surface of the red brick and tile according to the surface quality defect coefficient are as follows:

[0015]

[0016] In the formula, Qj is the surface quality defect coefficient, fv and fc are the reflection intensity non-uniformity coefficient and the phase anomaly change coefficient respectively, b1 and b2 are the preset proportional values of fv and fc respectively, and both b1 and b2 are greater than 0;

[0017] Compare the surface quality defect coefficient with the preset surface quality defect coefficient threshold. If the surface quality defect coefficient is not less than the preset surface quality defect coefficient threshold, it means that there are quality problems on the surface of the red brick and tile, and a first-level alarm is issued;

[0018] If the surface quality defect coefficient is less than the preset surface quality defect coefficient threshold, it means that there are no quality problems on the surface of the red brick and tile, and it is necessary to further analyze and judge whether there are defects inside the brick and tile.

[0019] Optionally, when there are no quality problems on the surface of the red brick and tile, emit ultrasonic waves to the red brick and tile to further judge whether there are quality problems inside the red brick and tile. The specific steps are as follows:

[0020] After the detection light is emitted by the ultrasonic probe and penetrates the brick and tile, the probe at the other end receives the acoustic signal, and the received acoustic signal is preprocessed and normalized to obtain the target signal;

[0021] Feature extraction is performed on the target signal, including the energy loss coefficient, the signal broadening coefficient, and the frequency shift coefficient, and the contact state coefficient is obtained according to the energy loss coefficient, the signal broadening coefficient, and the frequency shift coefficient;

[0022] The contact state coefficient is compared with the preset contact state coefficient threshold, and whether the contact between the probe and the surface of the brick and tile is qualified is judged according to the comparison result;

[0023] When the contact between the probe and the surface of the brick and tile is qualified, the defect characteristics in the target signal are analyzed to judge whether there are internal defects in the brick and tile, and the quality inspection of the brick and tile is carried out.

[0024] Optionally, the calculation steps of the energy loss coefficient are as follows:

[0025] The ultrasonic signal emitted by the probe is recorded as the original signal, and the duration of the emission of the original signal is obtained, and the total energy of the input ultrasonic signal is calculated. The calculation formula is: In the formula, WS is the total energy of the input ultrasonic signal, T is the duration, and S in (t) represents the instantaneous amplitude of the ultrasonic signal emitted by the probe;

[0026] The target signal received by the detector at the other end is obtained, and the total energy of the target signal is analyzed and calculated. The calculation formula is: In the formula, WK is the total energy of the received ultrasonic signal, T is the duration, and S ou (t) represents the instantaneous amplitude of the target signal;

[0027] The energy loss coefficient ZX is calculated. The calculation formula is: In the formula, ZX is the energy loss coefficient.

[0028] Optionally, the calculation steps of the signal broadening coefficient are as follows:

[0029] Envelope extraction is performed on the target signal, and envelope extraction is performed through Hilbert transform to obtain the envelope of the target signal;

[0030] The full width at half maximum FWHM of the envelope is calculated. The calculation formula is: FWHM = t2 - t1; t1 and t2 are the start and end times when the signal envelope drops to half of the maximum value respectively;

[0031] The duration RH of the signal envelope is calculated, that is, the total time length of the signal envelope from the starting point to the ending point. The calculation formula is: RH = t end -tstart , t end and t start are the start time and end time of the envelope signal, respectively;

[0032] Calculate the signal broadening coefficient, and the calculation formula is: In the formula, BN is the signal broadening coefficient.

[0033] Optionally, the calculation steps of the frequency offset coefficient are:

[0034] Perform a fast Fourier transform on the target signal to transform the target signal into the frequency domain to obtain the spectrum S(f); f is the frequency;

[0035] Calculate the center frequency f0 of the signal spectrum, and the calculation formula is:

[0036]

[0037] In the formula, |S(f)| 2 is the power density of the spectrum, indicating the energy distribution of the signal in the frequency domain;

[0038] According to the center frequency f0 and the preset ideal frequency f d Calculate the frequency offset Δf, and the calculation formula is: Δf = f0 - f d ; Calculate the frequency offset coefficient according to the frequency offset Δf, and the calculation formula is: In the formula, CX is the frequency offset coefficient.

[0039] Optionally, the steps to obtain the contact state coefficient according to the energy loss coefficient, the signal broadening coefficient and the frequency offset coefficient are:

[0040]

[0041] In the formula, DFR is the contact state coefficient, ZX, BN and CX are the energy loss coefficient, the signal broadening coefficient and the frequency offset coefficient respectively, a1, a2, a3 are the preset proportional values of ZX, BN and CX respectively, and a1, a2, a3 are all greater than 0;

[0042] The steps to judge whether the contact between the probe and the brick and tile surface is qualified according to the comparison result are:

[0043] Compare the contact state coefficient with the preset contact state coefficient threshold. If the contact state coefficient is less than the preset contact state coefficient threshold, it means that the contact between the probe and the brick and tile surface is qualified;

[0044] If the contact state coefficient is not less than the preset contact state coefficient threshold, it indicates that the contact between the probe and the brick and tile surface is unqualified. An alarm is issued and an acoustic wave signal is re-emitted until the contact state coefficient is less than the preset contact state coefficient threshold.

[0045] Optionally, when the contact between the probe and the brick and tile surface is qualified, the steps of analyzing the defect characteristics in the target signal, judging whether there are internal defects in the brick and tile, and performing quality inspection on the brick and tile are as follows:

[0046] The defect characteristics in the target signal include energy entropy and maximum amplitude value;

[0047] Divide the target signal into multiple small segments for individual analysis of each segment;

[0048] Calculate the energy of each segment of the signal: For each segment of the signal, calculate its energy; the calculation method of energy is the average value of the square of the signal amplitude;

[0049] Normalize the energy of each segment of the signal to obtain the probability distribution of energy, that is, the proportion of the energy of each segment of the signal in the total energy;

[0050] Calculate the energy entropy. The formula for energy entropy is: In the formula, HNK is the energy entropy, p j represents the proportion of the energy of the j-th segment of the signal, and M is the total number of signal segments;

[0051] Normalize the energy entropy and maximum amplitude value of the target signal, and obtain the internal defect coefficient according to the normalized energy entropy and maximum amplitude value of the target signal. Compare the internal defect coefficient with the preset internal defect coefficient threshold. If the internal defect coefficient is not less than the preset internal defect coefficient threshold, there are defects inside the brick and tile; otherwise, there are no defects.

[0052] In the second aspect of the implementation of the present invention, a quality inspection system for bricks and tiles is proposed. The system includes:

[0053] Reflection intensity non-uniformity module: Emits a laser to scan the surface of the red brick and tile, and calculates the reflection intensity non-uniformity coefficient according to the strength of the reflection signal; evaluates whether the distribution of the reflection signal on the brick and tile surface is uniform;

[0054] Phase abnormal change module: Obtains the phase of the reflection signal, and calculates the phase abnormal change coefficient according to the phase of the reflection signal; evaluates the abnormal fluctuation of the phase of the reflection signal on the brick and tile surface;

[0055] Quality inspection module: Obtains the surface quality defect coefficient according to the reflection intensity non-uniformity coefficient and the phase abnormal change coefficient, and judges whether there are quality problems on the surface of the red brick and tile according to the surface quality defect coefficient.

[0056] The beneficial effects of the present invention:

[0057] The present invention provides a quality inspection method and system for bricks and tiles. First, a laser is emitted onto the surface of the red bricks and tiles to scan the surface, and whether there are quality problems on the surface of the red bricks and tiles is judged according to the strength and phase of the reflected signal. When there are no quality problems on the surface of the red bricks and tiles, ultrasonic waves are emitted to the red bricks and tiles to further judge whether there are quality problems inside the red bricks and tiles. Compared with detecting whether there are quality problems on the red bricks and tiles through image detection, this method based on laser scanning and ultrasonic detection has significant advantages. First of all, laser scanning can accurately obtain the detailed information on the surface of the bricks and tiles, and judge whether the surface is flat according to the strength and phase of the reflected signal, avoiding the influence of factors such as illumination, angle, and surface reflection in traditional image detection. Secondly, ultrasonic technology can penetrate deep into the interior of the bricks and tiles to detect potential defects under the surface, such as cracks and holes, which are difficult to identify by image detection. In addition, the combination of laser and ultrasonic makes the quality inspection process of bricks and tiles more comprehensive, which can not only ensure the surface quality, but also evaluate the internal defects with high precision, thus improving the accuracy and reliability of the overall detection. Brief Description of the Drawings

[0058] The present invention will be further described below with reference to the accompanying drawings.

[0059] Figure 1 is a flowchart of a quality inspection method for bricks and tiles;

[0060] Figure 2 is a framework diagram of a quality inspection system for bricks and tiles. Detailed Embodiments

[0061] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0062] All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0063] The embodiments of the present invention provide a quality inspection method for bricks and tiles. Refer to Figure 1 , Figure 1 is a flowchart of a quality inspection method for bricks and tiles provided by an embodiment of the present invention. The method includes the following steps:

[0064] By emitting laser light onto the surface of red bricks and tiles to scan the surface, and calculating the reflection intensity non-uniformity coefficient based on the strength of the reflected signal; evaluating whether the distribution of the reflected signal on the surface of the bricks and tiles is uniform;

[0065] Obtain the phase of the reflected signal, and calculate the phase anomaly change coefficient based on the phase of the reflected signal; evaluate the abnormal fluctuation of the phase of the reflected signal on the surface of the bricks and tiles

[0066] Obtain the surface quality defect coefficient based on the reflection intensity non-uniformity coefficient and the phase anomaly change coefficient, and determine whether there are quality problems on the surface of the red bricks and tiles according to the surface quality defect coefficient.

[0067] Based on a quality inspection method for bricks and tiles provided by an embodiment of the present invention, through the above method, high-precision and comprehensive inspection of the quality of bricks and tiles can be achieved, and the occurrence of misdetection or missed detection can be reduced.

[0068] In one embodiment, by emitting laser light onto the surface of red bricks and tiles to scan the surface, and calculating the reflection intensity non-uniformity coefficient based on the strength of the reflected signal, evaluating whether the distribution of the reflected signal on the surface of the bricks and tiles is uniform;

[0069] Specifically, the reflection intensity non-uniformity coefficient is a parameter that measures the degree of change in the strength of the reflected signal on the surface of bricks and tiles. It is used to describe whether the distribution of the reflected light intensity on the surface of bricks and tiles is uniform, reflecting changes, defects or irregularities in the surface structure; when there are defects such as cracks, depressions, and particles on the surface, the reflected signal will be affected, resulting in non-uniform reflection intensity in different regions. When there are cracks, depressions, pores or other structural defects on the surface of bricks and tiles, these defects will cause light scattering or absorption, changing the intensity of the reflected signal. For example: light reflection at cracks will show a scattering phenomenon, making the reflected signal intensity non-uniform; pores or irregular holes will cause non-uniform distribution of the reflected light; an increase in surface roughness will cause the reflected light to scatter, resulting in non-uniform intensity; in the absence of defects, the surface of bricks and tiles is smoother, and the light reflection is more uniform. As the surface defects (such as cracks, depressions, pores, etc.) increase, the reflection of surface light changes, resulting in non-uniform distribution of the reflection intensity. An increase in the reflection intensity non-uniformity coefficient means that the surface defects are more obvious, which may affect the strength and durability of the bricks and tiles, thus determining that there are quality problems with the bricks and tiles;

[0070] Specifically, the calculation steps of the reflection intensity non-uniformity coefficient are as follows:

[0071] Emit laser light onto the surface of the bricks and tiles, and receive the reflected signal; according to different positions in the scanned area (assuming there are n positions in the scanned area), extract the reflection intensity values corresponding to the positions;

[0072] Calculate the mean and standard deviation of all the reflection intensity values, and divide the standard deviation by the mean to obtain the reflection intensity non-uniformity coefficient.

[0073] In one implementation, the advantage of analyzing the reflection intensity non-uniformity coefficient for judging whether there are quality problems on the surface of bricks and tiles is that it can quantify the uniformity of the reflected light on the surface of bricks and tiles, and then reveal the abnormalities of the surface microstructure. When there are cracks, pores, depressions or other defects on the surface of bricks and tiles, the intensity of the reflected light will change irregularly, resulting in an increase in the reflection intensity non-uniformity coefficient. Through this index, potential quality problems on the surface can be accurately detected without directly relying on naked-eye observation.

[0074] In one embodiment, the phase of the reflection signal is obtained, and the phase anomaly change coefficient is calculated according to the phase of the reflection signal;

[0075] The phase anomaly change coefficient refers to quantifying the abnormal fluctuation of the surface phase by calculating the degree of difference in the phase change of each area on the surface of bricks and tiles. This coefficient evaluates the height change of the surface of bricks and tiles at different positions by analyzing the phase difference of the laser reflection signal, so as to reveal possible defects. When the phase change is too large or irregular, it indicates that there may be major structural problems in the surface of this area, such as cracks, depressions, bulges, etc. Specifically, the phase anomaly change coefficient can be formed into a quantitative index by differentiating the phase values of each area of bricks and tiles from the phase of the uniform area. For example, when the phase offset value of a certain area exceeds the preset threshold, the phase anomaly change coefficient of this area will become larger, indicating that there are quality problems in this area. The increase of this coefficient usually means that the surface structure of this area is abnormal. On the contrary, it means that the surface of bricks and tiles is relatively uniform and the possibility of quality problems is low. In this way, high-precision quality detection can be realized, tiny surface changes can be identified, and the accuracy and reliability of brick and tile defect detection can be improved.

[0076] Specifically, the calculation steps of the phase anomaly change coefficient are as follows:

[0077] Emit laser light to the surface of bricks and tiles and receive the reflected signal; extract the phase values of the reflected signals at the corresponding positions according to different positions in the scanned area;

[0078] Calculate the mean value of the phase values of all the reflected signals, calculate the absolute difference between the phase value of each reflected signal and the mean value, and calculate the sum of all the absolute differences to obtain the phase anomaly change coefficient.

[0079] In one implementation manner, the advantages of analyzing the phase anomaly change coefficient for determining whether there are quality problems on the surface of bricks and tiles are as follows: The phase anomaly change coefficient can accurately reflect the minute height fluctuations and structural changes on the surface of bricks and tiles. Compared with simple reflection intensity analysis, it can more sensitively detect defects such as cracks, depressions, and protrusions, and even subtle quality problems that are difficult to detect by the naked eye can be identified. In addition, this coefficient has strong anti-interference ability, can reduce the detection errors caused by environmental light changes or surface color differences, and improve the stability and reliability of detection. Through the calculation of the phase anomaly change coefficient, a more refined quality assessment of the brick and tile surface can be achieved.

[0080] In one embodiment, the steps of obtaining the surface quality defect coefficient based on the reflection intensity non-uniformity coefficient and the phase anomaly change coefficient, and determining whether there are quality problems on the surface of red bricks and tiles according to the surface quality defect coefficient are as follows:

[0081]

[0082] In the formula, Qj is the surface quality defect coefficient, fv and fc are the reflection intensity non-uniformity coefficient and the phase anomaly change coefficient respectively, b1 and b2 are the preset proportional values of fv and fc respectively, and both b1 and b2 are greater than 0;

[0083] Compare the surface quality defect coefficient with the preset surface quality defect coefficient threshold. If the surface quality defect coefficient is not less than the preset surface quality defect coefficient threshold, it indicates that there are quality problems on the surface of red bricks and tiles, and a first-level alarm is issued;

[0084] If the surface quality defect coefficient is less than the preset surface quality defect coefficient threshold, it indicates that there are no quality problems on the surface of red bricks and tiles, and it is necessary to further analyze and determine whether there are defects inside the bricks and tiles.

[0085] It should be noted that b1 and b2 are set by professionals according to the actual situation. Generally, the sum of b1 and b2 is 1. For example, b1 and b2 can be 0.5 and 0.5 respectively, or other numbers, and there is no specific limitation; in addition, the preset surface quality defect coefficient threshold is set by professionals according to the actual situation, and there is no specific limitation and elaboration.

[0086] It should be noted that when the surface quality defect coefficient is not less than the preset surface quality defect coefficient threshold, it indicates that there are significant abnormalities in the optical reflection characteristics of the brick and tile surface, which may indicate quality problems such as cracks, depressions, bulges, and wear on the surface; therefore, it is necessary to immediately mark the brick and tile as a non-conforming product and issue a first-level alarm to prompt the need for further manual re-inspection or rejection of the product; when the surface quality defect coefficient is less than the preset surface quality defect coefficient threshold, it indicates that the quality of the brick and tile surface is relatively uniform and no obvious defects are detected; however, since optical detection mainly targets surface features and cannot judge the internal quality of the brick and tile, in this case, it is necessary to further use ultrasonic detection to analyze whether there are hidden defects such as cavities and fissures in the internal structure of the brick and tile to ensure the overall quality is qualified. This method can effectively screen the quality of brick and tile in layers, first quickly identify surface defects through laser scanning to improve the detection efficiency, and then perform ultrasonic detection on the bricks and tiles with qualified surfaces to ensure the integrity of the internal structure, thereby improving the quality reliability of the final product.

[0087] In one embodiment, when there are no quality problems on the surface of the red brick and tile, ultrasonic waves are emitted to the red brick and tile to further determine whether there are quality problems inside. The specific steps are as follows:

[0088] After the ultrasonic probe emits detection light to penetrate the brick and tile, the other end probe receives the acoustic signal, and the received acoustic signal is preprocessed and normalized to obtain the target signal;

[0089] Feature extraction is performed on the target signal, including the energy loss coefficient, signal broadening coefficient, and frequency shift coefficient, and the contact state coefficient is obtained based on the energy loss coefficient, signal broadening coefficient, and frequency shift coefficient;

[0090] The contact state coefficient is compared with the preset contact state coefficient threshold, and whether the contact between the probe and the brick and tile surface is qualified is judged according to the comparison result;

[0091] When the contact between the probe and the brick and tile surface is qualified, the defect characteristics in the target signal are analyzed to judge whether there are internal defects in the brick and tile, and the quality of the brick and tile is detected.

[0092] In one embodiment, after the ultrasonic probe emits detection light to penetrate the brick and tile, the acquisition signal is obtained, and the acquisition signal is preprocessed and normalized to obtain the preprocessed signal;

[0093] Specifically, the operations of preprocessing and normalization include: First, a low-pass filter is used to remove high-frequency noise and low-frequency interference in the ultrasonic signal to improve the signal clarity. Then, wavelet transform or fast Fourier transform (FFT) is adopted to perform spectral analysis on the signal, extract the main frequency components, and eliminate irrelevant noise. Next, the signal is intercepted with a time window to ensure that the extracted ultrasonic signal only contains the effective echo part and avoid the influence of external interference on subsequent analysis. Subsequently, a signal normalization method (such as min-max normalization or Z-score standardization) is used to adjust the signal amplitude to make it within a unified numerical range, reduce errors under different measurement environments, and improve the data consistency. The advantage of such operations is that it can effectively eliminate external interference and equipment noise, make the signal more stable, enhance the comparability between different brick and tile samples, improve the accuracy of subsequent feature extraction and analysis, and ensure the reliability and stability of the final detection results.

[0094] In one embodiment, feature extraction is performed on the preprocessed signal, including the energy loss coefficient, signal broadening coefficient, and frequency shift coefficient, and the contact state coefficient is obtained from the energy loss coefficient, signal broadening coefficient, and frequency shift coefficient;

[0095] It should be noted that due to the differences in interface acoustic characteristics and the instability of mechanical contact, there may be a problem of poor contact between the probe and the brick surface; when the probe has poor contact with the brick surface, strong reflection occurs at the interface of the ultrasonic wave, resulting in the acoustic wave being unable to effectively enter the brick body, thus affecting the detection accuracy; this may lead to two misjudgment situations: one is misjudging that there are defects inside the brick and tile, such as cracks or pores, although there are actually no defects; the other is covering up the real defects, making the internal damage not be effectively detected and causing missed detection; therefore, a method is needed to comprehensively analyze the ultrasonic signal, distinguish the abnormal signal caused by poor probe contact from the real brick and tile quality problems, so as to improve the detection reliability and avoid misjudgment caused by poor contact.

[0096] Specifically, feature extraction is performed on the preprocessed signal, including the energy loss coefficient, signal broadening coefficient, and frequency shift coefficient, and the contact state coefficient of the contact between the probe and the brick surface is obtained from the energy loss coefficient, signal broadening coefficient, and frequency shift coefficient;

[0097] Among them, the energy loss coefficient refers to the proportion of energy attenuation of ultrasonic signals during propagation due to factors such as interface reflection, absorption, and scattering. It can be used to measure the effective propagation degree of ultrasonic waves inside bricks and tiles. When the probe is in poor contact with the brick surface, a large acoustic impedance mismatch will form between the interfaces, causing a large amount of ultrasonic waves to be reflected back to the probe at the interface and failing to effectively enter the interior of the brick. This will lead to a significant decrease in the energy of the received transmitted signal, thereby increasing the energy loss coefficient. Therefore, the larger the energy loss coefficient, usually the worse the acoustic wave coupling between the probe and the brick surface, and the higher the possibility of poor contact. If not corrected, this poor contact may be misinterpreted as a defect inside the bricks and tiles, thus affecting the accuracy of the detection. Therefore, analyzing the change of the energy loss coefficient helps to distinguish poor contact from real defects inside the brick body and improve the reliability of the detection.

[0098] Specifically, the calculation steps of the energy loss coefficient are as follows:

[0099] Record the ultrasonic signal emitted by the probe as the original signal, obtain the duration of the original signal emission, and calculate the total energy of the input ultrasonic signal. The calculation formula is: In the formula, WS is the total energy of the input ultrasonic signal, T is the duration, and S in (t) represents the instantaneous amplitude of the ultrasonic signal emitted by the probe;

[0100] Obtain the target signal received by the detector at the other end, and analyze and calculate the total energy of the received signal (target signal). The calculation formula is: In the formula, WK is the total energy of the received ultrasonic signal, T is the duration, and S ou (t) represents the instantaneous amplitude of the target signal;

[0101] Calculate the energy loss coefficient ZX. The calculation formula is: In the formula, ZX is the energy loss coefficient.

[0102] In one implementation method, the benefits of analyzing the energy loss coefficient for judging whether the probe and the brick surface misjudge the internal defects of bricks and tiles due to poor contact are as follows: The energy loss coefficient can effectively quantify the energy attenuation of ultrasonic signals at the brick and tile surface interface, so as to accurately identify the signal loss caused by poor contact between the probe and the brick surface. By calculating the energy loss coefficient, it is possible to avoid misinterpreting the energy drop as cracks or pores inside the bricks and tiles due to the probe not being fully attached to the brick surface, thereby reducing the misjudgment rate; in addition, this coefficient can also provide real-time feedback to guide the detection equipment for automatic adjustment to ensure good contact between the probe and the brick surface, improve the stability and accuracy of ultrasonic detection, and thus more reliably identify the real quality defects inside the bricks and tiles.

[0103] In one embodiment, feature extraction is performed on the preprocessed signal, and it further includes a signal broadening coefficient;

[0104] It should be noted that the signal broadening coefficient refers to the degree of expansion of the signal spectrum during the propagation of the ultrasonic signal due to uneven interfaces, poor probe contact, or physical property differences of bricks and tiles; when the ultrasonic wave passes through the interface of bricks and tiles, if the interface is not smooth or the contact is incomplete, the sound wave will scatter and diffract during propagation, resulting in the broadening of the time-domain waveform of the signal. The larger the signal broadening coefficient, the higher the degree of energy diffusion of the signal, indicating that there is poor contact between the probe and the brick surface, resulting in abnormal signal propagation and affecting the accuracy of detection. A relatively large signal broadening coefficient is usually a sign of poor probe contact, meaning that part of the energy of the ultrasonic signal is lost during reflection and propagation at the interface, which may lead to the failure to detect real internal defects of bricks and tiles or misidentifying them as defects. Therefore, by analyzing the signal broadening coefficient, it is possible to effectively determine whether the contact between the ultrasonic probe and the brick surface is good and avoid misjudgment caused by poor contact.

[0105] Specifically, the calculation steps of the signal broadening coefficient are as follows:

[0106] Perform envelope extraction on the target signal. Envelope extraction is performed through Hilbert transform to obtain the envelope of the target signal, which reflects the intensity change of the ultrasonic signal;

[0107] Calculate the full width at half maximum FWHM of the envelope. The calculation formula is: FWHM = t2 - t1; t1 and t2 are respectively the start and end times when the signal envelope drops to half of the maximum value;

[0108] Calculate the duration RH of the signal envelope, that is, the total time length from the starting point to the ending point of the signal envelope. The calculation formula is: RH = t end -t start , t end and t start are respectively the starting time and ending time of the envelope signal;

[0109] Calculate the signal broadening coefficient. The calculation formula is: In the formula, BN is the signal broadening coefficient.

[0110] It should be noted that the main purpose of envelope extraction through Hilbert transform is to extract the instantaneous amplitude (i.e., envelope) from the original signal, which can effectively reflect the change of signal intensity over time. In the analysis of ultrasonic signals, envelope extraction can eliminate the influence of high-frequency components and focus on the energy change of the signal, making the broadening characteristics of the signal more obvious and accurate. Using Hilbert transform can better capture the non-stationarity of the signal. Especially when the signal is broadened, the change of the envelope can help reveal the signal attenuation and expansion caused by reasons such as uneven interfaces and poor contacts. By calculating the signal broadening coefficient in this way, not only can the detection accuracy be improved, but also the interference of noise and high-frequency components to the results can be reduced.

[0111] In one implementation, the advantage of analyzing the signal broadening coefficient for judging whether the probe and the brick surface misjudge the internal defects of the brick and tile due to poor contact is as follows: By analyzing the broadening degree of the signal, the signal scattering and diffraction phenomena caused by reasons such as uneven interfaces and incomplete probe contact can be identified; when the signal broadening coefficient is large, it indicates that the ultrasonic signal has experienced large energy loss and waveform distortion during propagation, which is usually a sign of poor contact between the probe and the brick and tile surface. If the contact is poor, the signal cannot be accurately transmitted and reflected, which may misjudge the internal defects of the brick and tile or completely fail to detect potential problems. By analyzing the signal broadening coefficient, the misjudgment caused by poor contact can be effectively excluded, ensuring more accurate detection results, thereby improving the reliability of brick and tile quality detection, avoiding missed detection or misdetection, and ensuring that the detection results reflect the true quality of the brick and tile.

[0112] In one embodiment, feature extraction of the target signal further includes a frequency offset coefficient;

[0113] Among them, the frequency offset coefficient refers to the degree of frequency offset of the ultrasonic signal during propagation due to poor contact between the probe and the brick surface, uneven interface or physical property differences of the brick and tile materials. When the ultrasonic wave passes through the brick and tile interface, if the contact is poor or the interface is not smooth, it will cause phenomena such as reflection and scattering of the ultrasonic wave during propagation, resulting in frequency offset of the ultrasonic wave. The larger the frequency offset coefficient, the more obvious the frequency change of the ultrasonic signal, usually indicating that there is a problem with the contact between the probe and the brick surface. When the contact is incomplete or poor, the ultrasonic signal cannot be effectively transmitted, resulting in a more obvious frequency offset phenomenon, which may affect the accuracy and quality of the signal, and further affect the judgment of the internal defects of the brick and tile. Therefore, by analyzing the frequency offset coefficient, the quality of the contact between the probe and the brick surface can be effectively judged, thereby ensuring the accuracy of the detection results and avoiding misjudgment or missed detection caused by poor contact.

[0114] Specifically, the calculation steps of the frequency offset coefficient are as follows:

[0115] Perform a fast Fourier transform on the target signal to transform the target signal into the frequency domain and obtain the spectrum S(f); f is the frequency;

[0116] Calculate the center frequency f0 of the signal spectrum, that is, the frequency weighted average of the signal; the center frequency reflects the main frequency components of the signal; the calculation formula is:

[0117]

[0118] In the formula, |S(f)| 2 is the power density of the spectrum, indicating the energy distribution of the signal in the frequency domain;

[0119] According to the center frequency f0 and the preset ideal frequency f d Calculate the frequency offset Δf, and the calculation formula is: Δf = f0 - f d ; Calculate the frequency offset coefficient according to the frequency offset Δf, and the calculation formula is: In the formula, CX is the frequency offset coefficient.

[0120] It should be noted that the preset ideal frequency refers to the standard frequency that the ultrasonic signal should have under ideal experimental conditions when the ultrasonic probe is in good contact with the brick and tile surface and there are no other interference factors. This frequency is usually determined through experimental calibration or based on a theoretical model, representing the expected frequency of the signal under normal propagation conditions. When the propagation of the ultrasonic signal is not interfered, the frequency of the signal should be close to this ideal value. If the frequency deviates, it may indicate poor contact between the probe and the brick surface or other factors affecting propagation. Therefore, the preset ideal frequency provides a benchmark for judging the probe contact state and signal quality; the specific preset ideal frequency is set by professionals according to the actual situation and will not be specifically limited and elaborated here.

[0121] In one implementation, the advantage of analyzing the frequency offset coefficient for judging whether the probe and the brick surface misjudge the internal defects of the brick and tile due to poor contact is as follows: The frequency offset coefficient reflects the degree of change in the frequency of the ultrasonic signal. Usually, under ideal propagation conditions, the frequency of the ultrasonic signal should be close to the preset ideal frequency. If the frequency offset coefficient is large, it indicates that the propagation of the signal has been affected abnormally, which may be due to incomplete contact between the probe and the brick surface or uneven interface, resulting in scattering or attenuation during signal propagation. This frequency offset not only affects the quality of the ultrasonic signal but also may lead to misjudgment or missed detection of internal defects, further affecting the accuracy of brick and tile quality inspection. By analyzing the frequency offset coefficient, the situation of poor contact can be identified in a timely manner, avoiding misjudgment caused by poor contact, thereby improving the reliability and accuracy of detection.

[0122] In one embodiment, the steps of obtaining the contact state coefficient based on the energy loss coefficient, the signal broadening coefficient, and the frequency offset coefficient are as follows:

[0123]

[0124] In the formula, DFR is the contact state coefficient, ZX, BN, and CX are the energy loss coefficient, the signal broadening coefficient, and the frequency offset coefficient respectively, a1, a2, and a3 are the preset proportional values of ZX, BN, and CX respectively, and a1, a2, and a3 are all greater than 0;

[0125] It should be noted that a1, a2, and a3 are set by professionals according to the actual situation. Generally, the sum of a1, a2, and a3 is 1. For example, a1, a2, and a3 can be 0.3, 0.4, 0.3 respectively, or other numbers, and the specific values are not limited.

[0126] In one embodiment, the steps of comparing the contact state coefficient with the preset contact state coefficient threshold and judging whether the contact between the probe and the brick and tile surface is qualified according to the comparison result are as follows:

[0127] Compare the contact state coefficient with the preset contact state coefficient threshold. If the contact state coefficient is less than the preset contact state coefficient threshold, it means that the contact between the probe and the brick and tile surface is qualified;

[0128] If the contact state coefficient is not less than the preset contact state coefficient threshold, it means that the contact between the probe and the brick and tile surface is unqualified, an alarm is issued and the acoustic wave signal is re-emitted until the contact state coefficient is less than the preset contact state coefficient threshold.

[0129] It should be noted that the preset contact state coefficient threshold is set by professionals according to the actual situation, and the specific values are not limited and will not be elaborated here.

[0130] It should be noted that by comparing the contact state coefficient with the preset contact state coefficient threshold, the contact quality between the ultrasonic probe and the brick and tile surface can be effectively judged. When the contact state coefficient is less than the preset threshold, it indicates that the contact between the probe and the brick and tile surface is good, and the ultrasonic signal can propagate smoothly, and the detection result is reliable. However, if the contact state coefficient does not meet the preset standard, it indicates that there is poor contact between the probe and the brick and tile surface, which may cause signal reflection or attenuation, thereby affecting the accuracy of the detection. Therefore, the system will issue an alarm and require the acoustic wave signal to be re-emitted until the contact state coefficient returns to the qualified level to ensure the reliability and accuracy of the detection. This process can effectively avoid misjudgment and missed detection caused by poor contact and ensure the accuracy of brick and tile quality detection.

[0131] In one embodiment, when the contact between the probe and the brick and tile surface is qualified, the steps of analyzing the defect characteristics in the target signal, judging whether there are internal defects in the brick and tile, and performing quality inspection on the brick and tile are as follows:

[0132] The defect characteristics in the target signal include energy entropy and maximum amplitude value;

[0133] Divide the target signal into multiple small segments for individual analysis of each segment.

[0134] Calculate the energy of each segment of the signal: For each segment of the signal, calculate its energy; the calculation of energy is usually the average value of the square of the signal amplitude;

[0135] Calculate the probability distribution: Normalize the energy of each segment of the signal to obtain the probability distribution of the energy, that is, the proportion of the energy of each segment of the signal in the total energy;

[0136] Calculate the energy entropy: Using the probability distribution of the energy, calculate the energy entropy. The formula for the energy entropy is: In the formula, HNK is the energy entropy, p j represents the proportion of the energy of the j-th segment of the signal, and M is the total number of signal segments;

[0137] Normalize the energy entropy and maximum amplitude value of the target signal, and obtain the internal defect coefficient based on the normalized energy entropy and maximum amplitude value of the target signal. Compare the internal defect coefficient with the preset internal defect coefficient threshold. If the internal defect coefficient is not less than the preset internal defect coefficient threshold, there are defects inside the brick and tile; otherwise, there are no defects.

[0138] It should be noted that energy entropy is a measure describing the uncertainty of information in a signal, which reflects the distribution of signal energy; the larger the energy entropy, the more complex the energy distribution of the signal, usually caused by inhomogeneities or defects (such as cracks, pores, loose areas, etc.) inside the brick and tile. These defects will cause changes in the sound wave propagation path, resulting in scattering and reflection of sound waves during propagation, thus generating more complex components in the frequency domain and time domain of the signal. As the severity of the defects increases, the more stray components appear in the signal, and the energy entropy also increases. Therefore, a higher energy entropy is often a sign of the existence of internal defects and can help judge the quality problems inside the brick and tile.

[0139] It should be noted that the maximum amplitude value refers to the maximum amplitude value in the signal, representing the signal intensity. The existence of defects may lead to enhanced signal reflection, thereby increasing the maximum value; the larger the maximum amplitude value, the higher the signal intensity, which is usually due to the reflection or scattering of ultrasonic signals when encountering obstacles or inhomogeneous media (such as defects like cracks and pores) during propagation, resulting in enhanced signal reflection intensity. Therefore, when the maximum amplitude value of the signal is relatively large, it may indicate the existence of defects inside the bricks and tiles, leading to increased signal reflection or diffraction. The existence of defects often changes the propagation path and reflection characteristics of sound waves, resulting in a relatively high amplitude of the received signal. Therefore, by analyzing the maximum amplitude value in the signal, the possibility of internal defects in bricks and tiles can be effectively judged.

[0140] It should be noted that the calculation steps for obtaining the internal defect coefficient based on the normalized energy entropy and maximum amplitude value of the target signal are as follows: In the formula, Bup is the internal defect coefficient, ut and tn are the energy entropy and maximum amplitude value of the target signal after normalization respectively, c1 and c2 are the preset proportional values of ut and tn respectively, and both c1 and c2 are greater than 0;

[0141] It should be noted that c1 and c2 are set by professionals according to the actual situation. Generally, the sum of c1 and c2 is 1. For example, c1 and c2 can be 0.5 and 0.5 respectively, or other numbers, and there is no specific limitation; in addition, the preset internal defect coefficient threshold is set by professionals according to the actual situation, and there is no specific limitation or elaboration.

[0142] In one implementation, in this way, first, a laser is emitted onto the surface of the red bricks and tiles to scan the surface of the bricks and tiles, and whether there are quality problems on the surface of the red bricks and tiles is judged according to the strength and phase of the reflected signal; when there are no quality problems on the surface of the red bricks and tiles, ultrasonic waves are emitted to the red bricks and tiles to further judge whether there are quality problems inside the red bricks and tiles. Compared with detecting whether there are quality problems in bricks and tiles through image detection, this method based on laser scanning and ultrasonic detection has significant advantages. First of all, laser scanning can accurately obtain the detailed information on the surface of the bricks and tiles, and judge whether the surface is flat according to the strength and phase of the reflected signal, avoiding the influence of factors such as illumination, angle and surface reflection in traditional image detection. Secondly, ultrasonic technology can penetrate deep into the bricks and tiles to detect potential defects under the surface, such as cracks and cavities, which are difficult to be easily identified by image detection. In addition, the combination of laser and ultrasonic waves makes the brick and tile quality detection process more comprehensive, which can not only ensure the surface quality, but also conduct high-precision evaluation of internal defects, thereby improving the accuracy and reliability of the overall detection.

[0143] An embodiment of the present invention also provides a quality inspection system for bricks and tiles based on the same inventive concept. Refer to Figure 2 , Figure 2 which is a framework diagram of a quality inspection system for bricks and tiles provided by an embodiment of the present invention. The system includes:

[0144] Reflected intensity non-uniformity module: Emits laser to scan the surface of red bricks and tiles, and calculates the reflected intensity non-uniformity coefficient according to the strength of the reflected signal; evaluates whether the distribution of the reflected signal on the surface of the bricks and tiles is uniform;

[0145] Phase abnormal change module: Obtains the phase of the reflected signal, and calculates the phase abnormal change coefficient according to the phase of the reflected signal; evaluates the abnormal fluctuation of the phase of the reflected signal on the surface of the bricks and tiles;

[0146] Quality inspection module: Obtains the surface quality defect coefficient according to the reflected intensity non-uniformity coefficient and the phase abnormal change coefficient, and judges whether there are quality problems on the surface of red bricks and tiles based on the surface quality defect coefficient. Based on the quality inspection system for bricks and tiles provided by an embodiment of the present invention, through the above method, high-precision and comprehensive detection of the quality of bricks and tiles can be achieved, and the occurrence of misdetection or missed detection can be reduced.

[0147] The above has described an embodiment of the present invention in detail, but the content described is only a preferred embodiment of the present invention and cannot be used to artificially limit the scope of implementation of the present invention. Any equal changes and improvements made according to the scope of the application of the present invention should still fall within the scope covered by the patent of the present invention.

Claims

1. A quality inspection method for bricks and tiles, characterized in that: The following steps are involved: The laser is emitted to the surface of red bricks and tiles to scan the surface of the bricks and tiles, and the reflection intensity unevenness coefficient is calculated according to the strength of the reflection signal; whether the distribution of the reflection signal on the surface of the bricks and tiles is uniform is evaluated; Obtain the phase of the reflected signal, and calculate the phase abnormal variation coefficient based on the phase of the reflected signal; evaluate the abnormal fluctuation of the phase of the reflected signal on the tile surface; The surface quality defect coefficient is obtained according to the reflection intensity non-uniformity coefficient and the phase abnormality variation coefficient, and it is judged whether there is quality problem on the surface of red bricks and tiles according to the surface quality defect coefficient.

2. A quality inspection method for bricks and tiles according to claim 1, characterized in that: The calculation steps of reflection intensity non-uniformity coefficient and phase abnormal variation coefficient are as follows: The laser is emitted to the surface of the bricks and tiles, the reflected signal is received, and the reflection intensity value of the corresponding position is extracted according to the different positions of the scanning area; Calculate the mean and standard deviation of all reflection intensity values, and divide the standard deviation by the mean to obtain the reflection intensity unevenness coefficient; The laser is emitted to the surface of the brick and tile, and the reflected signal is received; the phase value of the reflected signal at the corresponding position is extracted according to the different positions of the scanning area; The mean phase value of all reflected signals is calculated, and the absolute difference between the phase value of each reflected signal and the mean is calculated, and the sum of all absolute differences is calculated to obtain the phase abnormality variation coefficient.

3. A quality inspection method for bricks and tiles according to claim 1, characterized in that: The steps of obtaining the surface quality defect coefficient according to the reflection intensity non-uniformity coefficient and the phase abnormality variation coefficient and judging whether there is a quality problem on the surface of the red brick tile according to the surface quality defect coefficient are as follows: Where Qj is the surface quality defect coefficient, fv and fc are the reflection intensity non-uniformity coefficient and the phase abnormal variation coefficient, b1 and b2 are the preset ratio values ​​of fv and fc, and b1 and b2 are both greater than 0; The surface quality defect coefficient is compared with a preset surface quality defect coefficient threshold. If the surface quality defect coefficient is not less than the preset surface quality defect coefficient threshold, it indicates that there is a quality problem on the surface of the red brick and tile, and a first-level alarm is issued; If the surface quality defect coefficient is less than the preset surface quality defect coefficient threshold, it means that there is no quality problem on the surface of the red brick and tile, and further analysis is needed to determine whether there are defects inside the brick and tile.

4. A quality inspection method for bricks and tiles according to claim 3, characterized in that: When there is no quality problem on the surface of the red brick tile, ultrasonic waves are emitted to the red brick tile to further determine whether there is a quality problem inside the red brick tile. The specific steps are as follows: After the ultrasonic probe transmits the detection light to penetrate the bricks and tiles, the other end of the probe receives the sound wave signal, and the received sound wave signal is pre-processed and normalized to obtain the target signal; Extracting features of the target signal, including energy loss coefficient, signal broadening coefficient and frequency shift coefficient, and obtaining a contact state coefficient according to the energy loss coefficient, signal broadening coefficient and frequency shift coefficient; Compare the contact state coefficient with the preset contact state coefficient threshold, and judge whether the contact between the probe and the tile surface is qualified according to the comparison result; When the contact between the probe and the brick and tile surface is qualified, the defect characteristics in the target signal are analyzed to determine whether the brick and tile have internal defects, and the quality of the brick and tile is inspected.

5. A quality inspection method for bricks and tiles according to claim 4, characterized in that: The calculation steps of the energy loss coefficient are: The ultrasonic signal emitted by the probe is recorded as the original signal, and the duration of the original signal emission is obtained. The total energy of the input ultrasonic signal is calculated using the following formula: Where WS is the total energy of the input ultrasonic signal, T is the duration, S in (t) represents the instantaneous amplitude of the ultrasonic signal emitted by the probe; Obtain the target signal received by the detector at the other end, and analyze and calculate the total energy of the target signal. The calculation formula is: Where WK is the total energy of the received ultrasonic signal, T is the duration, S ou (t) represents the instantaneous amplitude of the target signal; Calculate the energy loss coefficient ZX, the calculation formula is: Where ZX is the energy loss coefficient.

6. A quality inspection method for bricks and tiles according to claim 4, characterized in that: The calculation steps of the signal broadening coefficient are: Extract the envelope of the target signal by Hilbert transform to obtain the envelope of the target signal; Calculate the full width half maximum value FWHM of the envelope. The calculation formula is: FWHM = t2-t1; t1 and t2 are the start and end times when the signal envelope drops to half of the maximum value, respectively; Calculate the duration RH of the signal envelope, that is, the total time length of the signal envelope from the starting point to the end point. The calculation formula is: RH = t end -t start , t end and t start are the start time and end time of the envelope signal respectively; Calculate the signal broadening coefficient, the calculation formula is: Where BN is the signal broadening coefficient.

7. A quality inspection method for bricks and tiles according to claim 4, characterized in that: The calculation steps of the frequency offset coefficient are: Perform fast Fourier transform on the target signal, transform the target signal into the frequency domain, and obtain the spectrum S(f); f is the frequency; Calculate the center frequency f0 of the signal spectrum. The calculation formula is: Where |S(f)| 2 is the power density of the spectrum, which indicates the energy distribution of the signal in the frequency domain; According to the center frequency f0 and the preset ideal frequency f d Calculate the frequency offset Δf. The calculation formula is: Δf = f0-f d ; Calculate the frequency offset coefficient according to the frequency offset Δf, and the calculation formula is: Where CX is the frequency offset coefficient.

8. A quality inspection method for bricks and tiles according to claim 4, characterized in that: The steps to obtain the contact state coefficient based on the energy loss coefficient, signal broadening coefficient and frequency shift coefficient are as follows: Wherein, DFR is the contact state coefficient, ZX, BN and CX are the energy loss coefficient, signal broadening coefficient and frequency shift coefficient respectively, a1, a2 and a3 are the preset ratio values ​​of ZX, BN and CX respectively, and a1, a2 and a3 are all greater than 0; The steps to determine whether the contact between the probe and the tile surface is qualified according to the comparison results are as follows: The contact state coefficient is compared with a preset contact state coefficient threshold. If the contact state coefficient is less than the preset contact state coefficient threshold, it indicates that the contact between the probe and the tile surface is qualified. If the contact state coefficient is not less than the preset contact state coefficient threshold, it means that the contact between the probe and the tile surface is unqualified, an alarm is issued and the sound wave signal is re-emitted until the contact state coefficient is less than the preset contact state coefficient threshold.

9. A quality inspection method for bricks and tiles according to claim 4, characterized in that: When the contact between the probe and the brick and tile surface is qualified, the defect characteristics in the target signal are analyzed to determine whether the brick and tile have internal defects. The steps for quality inspection of bricks and tiles are as follows: The defect characteristics in the target signal include energy entropy and maximum amplitude value; Divide the target signal into multiple small segments so that each segment can be analyzed separately; Calculate the energy of each signal segment: For each signal segment, calculate its energy; Energy is calculated as the average of the square of the signal amplitude; Normalize the energy of each signal segment to obtain the probability distribution of energy, that is, the proportion of each signal segment energy in the total energy; Calculate energy entropy. The formula for energy entropy is: Where HNK is the energy entropy, p j represents the energy proportion of the jth segment signal, and M is the total number of signal segments; The energy entropy and the maximum amplitude value of the target signal are normalized, and the internal defect coefficient is obtained based on the energy entropy and the maximum amplitude value of the normalized target signal. The internal defect coefficient is compared with the preset internal defect coefficient threshold. If the internal defect coefficient is not less than the preset internal defect coefficient threshold, there are defects inside the bricks and tiles; otherwise, there are no defects.

10. A quality inspection system for bricks and tiles, used to implement a quality inspection method for bricks and tiles as described in any one of claims 1 to 9, characterized in that: The system comprises: Reflection intensity unevenness module: Scans the surface of red bricks and tiles by emitting lasers to them, and calculates the reflection intensity unevenness coefficient based on the strength of the reflected signal; evaluates whether the distribution of the reflected signal on the brick and tile surface is uniform; Abnormal phase change module: obtains the phase of the reflected signal and calculates the abnormal phase change coefficient based on the phase of the reflected signal; evaluates the abnormal fluctuation of the phase of the reflected signal on the tile surface; Quality inspection module: obtain the surface quality defect coefficient according to the reflection intensity unevenness coefficient and the phase abnormality change coefficient, and judge whether there is any quality problem on the surface of the red brick tile according to the surface quality defect coefficient.

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