A method and system for quality inspection of bricks and tiles

Abstract

This invention discloses a method and system for quality inspection of bricks and tiles, relating to the field of brick and tile quality inspection technology. First, a laser is emitted to scan the surface of the red brick and tile to determine if any quality problems exist. If no quality problems are found on the surface, ultrasonic waves are emitted to further determine if any quality problems exist inside the brick and tile. Compared to detecting quality problems through images, laser scanning can accurately acquire detailed information about the brick and tile surface, avoiding the influence of factors such as lighting, angle, and surface reflection that may occur in traditional image detection. Ultrasonic technology can penetrate deep into the brick and tile to detect potential defects beneath the surface, such as cracks and voids. The combination of laser and ultrasonic waves makes the brick and tile quality inspection process more comprehensive, thereby improving the overall accuracy and reliability of the inspection.

Description

Technical Field

[0001] This invention relates to the field of brick and tile quality testing technology, and specifically to a method and system for testing the quality of bricks and tiles. Background Technology

[0002] The quality inspection of red bricks and tiles mainly involves multiple aspects, including appearance quality, physical properties, mechanical properties, and durability, to ensure they meet the requirements of building projects. Defect detection is a crucial part of the quality assessment. Appearance quality inspection primarily checks whether the shape of the bricks and tiles is regular, whether the dimensions meet standards, and whether there are defects such as cracks, missing corners, and warping on the surface. Internal defect detection focuses on factors that may affect the strength and durability of the bricks and tiles, such as pores, fissures, and inclusions. Furthermore, physical property testing includes measuring water absorption, density, and porosity to assess the bricks' impermeability and durability, as well as compressive and flexural strength, using a press to apply loads and determine their load-bearing capacity. Durability testing also includes frost resistance, weather resistance, acid and alkali resistance, and fire resistance testing, typically using freeze-thaw cycles, aging tests, chemical erosion tests, and firing tests at different temperatures to evaluate the stability and service life of the bricks and tiles under different environments. Through these comprehensive testing methods, the quality of red bricks and tiles can be fully assessed, ensuring their safety and reliability in building projects.

[0003] Among these, defect detection of bricks and tiles is a crucial part of quality assessment. Current methods involve acquiring images of the brick and tile surface and analyzing them to determine whether defects exist and whether the tiles meet standards. However, image detection relies primarily on surface features, making it difficult to detect hidden defects such as cracks, pores, or inclusions within the bricks and tiles, resulting in incomplete detection. Furthermore, image quality may be affected by factors such as lighting, shooting angle, and surface reflection, reducing detection accuracy. In addition, color variations or complex textures on the brick and tile surface may interfere with algorithmic judgment, leading to false positives or false negatives. Therefore, relying solely on image analysis is insufficient to achieve high-precision and comprehensive defect detection of bricks and tiles. Summary of the Invention

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

[0005] In a first aspect of this invention, a method for quality inspection of bricks and tiles is first proposed, the method comprising:

[0006] The surface of red bricks and tiles is scanned by emitting a laser, and the non-uniformity coefficient of reflection intensity is calculated based on the strength of the reflected signal; the uniformity of the distribution of reflected signals on the brick and tile surface is then evaluated.

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

[0008] The surface quality defect coefficient is obtained based on the non-uniformity coefficient of reflection intensity and the abnormal change coefficient of phase, and the surface quality defect coefficient is used to determine whether there are quality problems on the surface of red bricks and tiles.

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

[0010] A laser is emitted onto the surface of bricks and tiles, and the reflected signals are received. Based on different locations in the scanned area, the reflection intensity value at the corresponding location is extracted.

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

[0012] A laser is emitted onto the surface of bricks and tiles, and the reflected signals are received; the phase value of the reflected signal at different locations in the scanned area is extracted.

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

[0014] Optionally, the steps for obtaining the surface quality defect coefficient based on the reflection intensity non-uniformity coefficient and the phase anomaly change coefficient, and then determining whether there are quality problems on the surface of the red brick tile based on 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 phase anomaly change coefficient, respectively, and b1 and b2 are the preset ratio values ​​of fv and fc, respectively, and both b1 and b2 are greater than 0.

[0017] The surface quality defect coefficient is compared 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 is a quality problem on the surface of the red brick 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 is no quality problem on the surface of the red bricks and tiles, and further analysis is needed to determine whether there are defects inside the bricks and tiles.

[0019] Optionally, when there are no quality problems on the surface of the red bricks and tiles, ultrasonic waves can be emitted into the red bricks and tiles to further determine whether there are quality problems inside the tiles. The specific steps are as follows:

[0020] After the ultrasonic probe emits a probe light that penetrates the bricks and tiles, the other end of the probe receives the sound wave signal. The received sound wave signal is preprocessed and normalized to obtain the target signal.

[0021] Feature extraction is performed on the target signal, including energy loss coefficient, signal broadening coefficient, and frequency offset coefficient, and the contact state coefficient is obtained based on the energy loss coefficient, signal broadening coefficient, and frequency offset coefficient.

[0022] The contact state coefficient is compared with the preset contact state coefficient threshold, and the contact between the probe and the brick and tile surface is judged to be qualified based on the comparison results.

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

[0024] Optionally, the calculation steps for 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 original signal emission is obtained. The total energy of the input ultrasonic signal is calculated using the following formula: In the formula, WS is the total energy of the input ultrasonic signal, T is the duration, and S is the total energy of the input ultrasonic signal. in (t) represents the instantaneous amplitude of the ultrasonic signal emitted by the probe;

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

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

[0028] Optionally, the calculation steps for the signal broadening factor are as follows:

[0029] The envelope of the target signal is extracted by performing Hilbert transform.

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

[0031] The duration RH of the signal envelope, i.e., the total time length of the signal envelope from the start point to the end point, is calculated using the formula: RH = t end -tstart , t end and t start These are the start and end times of the envelope signal, respectively.

[0032] The formula for calculating the signal broadening factor is as follows: In the formula, BN is the signal broadening coefficient.

[0033] Optionally, the calculation steps for the frequency offset coefficient are as follows:

[0034] Perform a Fast Fourier Transform on the target signal to convert it to the frequency domain, obtaining the spectrum S(f); where f is the frequency.

[0035] The formula for calculating the center frequency f0 of the signal spectrum is as follows:

[0036]

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

[0038] Based on the center frequency f0 and the preset ideal frequency f d The frequency offset Δf is calculated using the formula: Δf = f0 - f d The frequency offset coefficient is calculated based on the frequency offset Δf, using the following formula: In the formula, CX is the frequency offset coefficient.

[0039] Optionally, the steps for obtaining the contact state coefficient based on the energy loss coefficient, signal broadening coefficient, and frequency offset coefficient are as follows:

[0040]

[0041] In the formula, DFR is the contact state coefficient, ZX, BN and CX are the energy loss coefficient, signal broadening coefficient and frequency offset coefficient respectively, and 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.

[0042] The steps to determine whether the contact between the probe and the brick / tile surface is qualified based on the comparison results are as follows:

[0043] The contact state coefficient is compared 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 surface is unqualified. An alarm will be issued and the sound wave signal will be 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 / tile surface is qualified, the defect characteristics in the target signal are analyzed to determine whether the brick / tile has internal defects. The steps for quality inspection of the brick / tile are as follows:

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

[0047] The target signal is divided into multiple segments so that each segment can be analyzed separately;

[0048] Calculate the energy of each signal segment: For each signal segment, calculate its energy; the energy is calculated as the average of the squared values ​​of the signal amplitude.

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

[0050] The formula for calculating energy entropy is: In the formula, HNK is the energy entropy, p j This represents the energy percentage of the j-th signal segment, where M is the total number of signal segments;

[0051] The energy entropy and maximum amplitude of the target signal are normalized, and the internal defect coefficient is obtained based on the normalized energy entropy and maximum amplitude of the 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, then there is a defect inside the brick; otherwise, there is no defect.

[0052] In a second aspect of the invention, a quality inspection system for bricks and tiles is provided, the system comprising:

[0053] The uneven reflection intensity module scans the surface of red bricks and tiles by emitting a laser and calculating the uneven reflection intensity coefficient based on the strength of the reflected signal; it evaluates whether the distribution of reflected signals on the brick and tile surface is uniform.

[0054] Phase anomaly change module: acquires the phase of the reflected signal and calculates the phase anomaly change coefficient based on the phase of the reflected signal; evaluates the abnormal fluctuation of the phase of the reflected signal on the brick and tile surface;

[0055] Quality inspection module: The surface quality defect coefficient is obtained based on the reflection intensity non-uniformity coefficient and the phase abnormal change coefficient, and the surface quality defect coefficient is used to determine whether there are quality problems on the surface of red bricks and tiles.

[0056] The beneficial effects of this invention are:

[0057] This invention proposes a method and system for quality inspection of bricks and tiles. First, a laser is emitted to scan the surface of the red bricks and tiles, and the strength and phase of the reflected signals are used to determine if any quality problems exist on the surface. If no quality problems are found on the surface, ultrasonic waves are emitted to further determine if any internal quality problems exist. Compared to image-based quality inspection, this laser scanning and ultrasonic testing method has significant advantages. First, laser scanning can accurately acquire detailed information about the brick and tile surface, determining surface flatness by the strength and phase of the reflected signals, avoiding the influence of factors such as lighting, angle, and surface reflection that can affect traditional image inspection. Second, ultrasonic technology can penetrate deep into the bricks and tiles, detecting potential defects beneath the surface, such as cracks and holes, which are difficult to identify with image inspection. Furthermore, the combination of laser and ultrasonic waves makes the brick and tile quality inspection process more comprehensive, ensuring both surface quality and high-precision assessment of internal defects, thereby improving the overall accuracy and reliability of the inspection. Attached Figure Description

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

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

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

[0061] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0062] Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without inventive effort are within the scope of protection of this invention.

[0063] This invention provides a method for quality inspection of bricks and tiles. See also... Figure 1 , Figure 1 A flowchart illustrating a quality inspection method for bricks and tiles, provided as an embodiment of the present invention. The method includes the following steps:

[0064] The surface of red bricks and tiles is scanned by emitting a laser, and the non-uniformity coefficient of reflection intensity is calculated based on the strength of the reflected signal; the uniformity of the distribution of reflected signals on the brick and tile surface is then evaluated.

[0065] The phase of the reflected signal is obtained, and the phase anomaly change coefficient is calculated based on the phase of the reflected signal; the abnormal fluctuation of the phase of the reflected signal on the brick and tile surface is evaluated.

[0066] The surface quality defect coefficient is obtained based on the non-uniformity coefficient of reflection intensity and the abnormal change coefficient of phase, and the surface quality defect coefficient is used to determine whether there are quality problems on the surface of red bricks and tiles.

[0067] Based on the quality inspection method for bricks and tiles provided in this embodiment of the invention, high-precision and comprehensive quality inspection of bricks and tiles can be achieved through the above method, reducing the occurrence of false detection or missed detection.

[0068] In one embodiment, the uniformity of the distribution of reflected signals on the brick and tile surface is evaluated by scanning the brick and tile surface with a laser emitted into it and calculating the reflection intensity non-uniformity coefficient based on the strength of the reflected signal.

[0069] Specifically, the reflection intensity non-uniformity coefficient is a parameter that measures the degree of variation in the intensity of reflected signals on the surface of bricks and tiles. It describes whether the distribution of 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, or particles on the surface, the reflected signal will be affected, leading to non-uniform reflection intensity in different areas. 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 exhibit scattering, making the reflected signal intensity non-uniform; pores or irregular holes will cause uneven distribution of reflected light; increased surface roughness will cause scattering of reflected light, resulting in non-uniform intensity. In the absence of defects, the surface of bricks and tiles is relatively smooth, and light reflection is relatively uniform. As surface defects (such as cracks, depressions, pores, etc.) increase, the reflection of surface light changes, leading to non-uniform distribution of 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 indicating a quality problem.

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

[0071] A laser is emitted onto the surface of bricks and tiles, and the reflected signals are received. Based on different locations within the scanned area (assuming there are n locations within the scanned area), the reflection intensity value at the corresponding location is extracted.

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

[0073] In one implementation, analyzing the reflection intensity non-uniformity coefficient is beneficial for determining whether there are quality problems on the surface of bricks and tiles because it quantifies the uniformity of reflected light, thereby revealing anomalies in the surface microstructure. When cracks, pores, depressions, or other defects exist on the surface of bricks and tiles, the intensity of reflected light will change irregularly, leading to an increase in the reflection intensity non-uniformity coefficient. This indicator allows for the accurate detection of potential surface quality problems without relying directly on visual observation.

[0074] In one embodiment, the phase of the reflected signal is obtained, and a phase anomaly change coefficient is calculated based on the phase of the reflected signal;

[0075] The phase anomaly change coefficient quantifies abnormal fluctuations in the surface phase by calculating the degree of difference in phase change across different regions of a brick or tile surface. This coefficient analyzes the phase differences in laser reflection signals to assess height variations at different locations on the brick or tile surface, thereby revealing potential defects. Excessive or irregular phase changes indicate significant structural problems in that area, such as cracks, dents, or bulges. Specifically, the phase anomaly change coefficient is a quantitative indicator formed by comparing the phase values ​​of different regions of the brick or tile with those of a uniform region. For example, when the phase shift value of a certain region exceeds a preset threshold, the phase anomaly change coefficient for that region becomes larger, indicating a quality problem in that area. An increase in this coefficient usually signifies an abnormal surface structure in that region; conversely, a decrease indicates a more uniform brick or tile surface and a lower probability of quality problems. This method enables high-precision quality inspection, identifies minute surface changes, and improves the accuracy and reliability of brick and tile defect detection.

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

[0077] A laser is emitted onto the surface of bricks and tiles, and the reflected signals are received; the phase value of the reflected signal at different locations in the scanned area is extracted.

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

[0079] In one implementation method, 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, dents, and protrusions, and even minute quality problems that are difficult to detect with the naked eye can be identified. In addition, this coefficient has strong anti-interference ability, which can reduce the detection error caused by changes in ambient light or surface color differences, and improve the stability and reliability of detection. By calculating the phase anomaly change coefficient, a more refined assessment of the surface quality of bricks and tiles can be achieved.

[0080] In one embodiment, the steps for obtaining the surface quality defect coefficient based on the reflection intensity non-uniformity coefficient and the phase anomaly change coefficient, and for determining whether there are quality problems on the surface of the red brick tile based on 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 phase anomaly change coefficient, respectively, and b1 and b2 are the preset ratio values ​​of fv and fc, respectively, and both b1 and b2 are greater than 0.

[0083] The surface quality defect coefficient is compared 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 is a quality problem on the surface of the red brick tile 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 means that there is no quality problem on the surface of the red bricks and tiles, and further analysis is needed to determine whether there are defects inside the bricks and tiles.

[0085] It should be noted that b1 and b2 are set by professionals based on 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. There are no specific restrictions. In addition, the preset surface quality defect coefficient threshold is set by professionals based on the actual situation. There are no specific restrictions or details.

[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 a significant anomaly in the optical reflection characteristics of the brick / tile surface, potentially suggesting quality issues such as cracks, dents, bulges, or wear. Therefore, the brick / tile should be immediately marked as a non-conforming product, and a Level 1 alarm should be issued, indicating the need for further manual re-inspection or rejection. When the surface quality defect coefficient is less than the preset surface quality defect coefficient threshold, it indicates that the surface quality of the brick / tile is relatively uniform, and no obvious defects have been detected. However, since optical inspection primarily targets surface features and cannot determine the internal quality of the brick / tile, ultrasonic testing is necessary in this case. This involves analyzing the internal structure of the brick / tile to identify hidden defects such as voids and cracks, ensuring overall quality compliance. This method can effectively screen brick / tile quality in layers. First, laser scanning quickly identifies surface defects, improving detection efficiency. Then, ultrasonic testing is performed on bricks / tiles with acceptable surfaces to ensure the integrity of the internal structure, thereby improving the reliability of the final product.

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

[0088] After the ultrasonic probe emits a probe light that penetrates the bricks and tiles, the other end of the probe receives the sound wave signal. The received sound wave signal is preprocessed and normalized to obtain the target signal.

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

[0090] The contact state coefficient is compared with the preset contact state coefficient threshold, and the contact between the probe and the brick and tile surface is judged to be qualified based on the comparison results.

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

[0092] In one embodiment, an ultrasonic probe emits detection light that penetrates bricks and tiles to obtain a collected signal. The collected signal is then preprocessed and normalized to obtain a preprocessed signal.

[0093] Specifically, the preprocessing and normalization operations include: First, using a low-pass filter to remove high-frequency noise and low-frequency interference from the ultrasonic signal to improve signal clarity. Then, wavelet transform or Fast Fourier Transform (FFT) is used to perform spectral analysis on the signal, extracting the main frequency components and eliminating irrelevant noise. Next, a time window is applied to the signal to ensure that the extracted ultrasonic signal contains only the effective echo portion, avoiding the influence of external interference on subsequent analysis. Subsequently, signal normalization methods (such as max-min normalization or Z-score normalization) are used to adjust the signal amplitude to a uniform numerical range, reducing errors under different measurement environments and improving data consistency. The advantage of this approach is that it effectively eliminates external interference and equipment noise, making the signal more stable, while enhancing the comparability between different brick and tile samples, improving the accuracy of subsequent feature extraction and analysis, and ensuring the reliability and stability of the final detection results.

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

[0095] It should be noted that due to differences in the acoustic properties of the interface and the instability of mechanical contact, poor contact may occur between the probe and the brick surface. When the probe and the brick surface have poor contact, the ultrasonic waves are strongly reflected at the interface, preventing the sound waves from effectively entering the brick and thus affecting the accuracy of the detection. This may lead to two types of misjudgments: first, misjudging the presence of defects inside the brick, such as cracks or pores, even when there are no actual defects; second, masking real defects, causing internal damage to go undetected and resulting in missed detections. Therefore, a method is needed to comprehensively analyze the ultrasonic signals, distinguish between abnormal signals caused by poor probe contact and genuine brick quality problems, thereby improving the reliability of the detection and avoiding misjudgments caused by poor contact.

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

[0097] The energy loss coefficient refers to the proportion of energy attenuation of an ultrasonic signal during propagation due to factors such as interface reflection, absorption, and scattering. It measures the effective propagation degree of ultrasonic waves within bricks and tiles. When the probe has poor contact with the brick surface, a significant acoustic impedance mismatch occurs at the interface, causing a large amount of ultrasonic waves to be reflected back to the probe at the interface, failing to effectively penetrate the brick. This results in a substantial decrease in the received transmitted signal energy, thus increasing the energy loss coefficient. Therefore, a larger energy loss coefficient generally indicates poorer acoustic coupling between the probe and the brick surface, and a higher probability of poor contact. Without correction, this poor contact may be mistaken for an internal defect in the brick, affecting the accuracy of the detection. Therefore, analyzing changes in the energy loss coefficient helps distinguish between poor contact and genuine internal brick defects, improving the reliability of the detection.

[0098] Specifically, the steps for calculating the energy loss coefficient are as follows:

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

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

[0101] The energy loss coefficient ZX is calculated using the following formula: In the formula, ZX is the energy loss coefficient.

[0102] In one implementation, analyzing the energy loss coefficient offers several advantages in determining whether poor contact between the probe and the brick surface leads to misjudgments of internal defects. The energy loss coefficient effectively quantifies the energy attenuation of the ultrasonic signal at the brick-tile interface, thus accurately identifying signal loss due to poor probe-brick contact. Calculating the energy loss coefficient avoids misinterpreting energy reduction as internal cracks or pores due to insufficient probe contact, thereby reducing the false positive rate. Furthermore, this coefficient provides real-time feedback, guiding the testing equipment to automatically adjust and ensure good probe-brick contact, improving the stability and accuracy of ultrasonic testing and thus more reliably identifying true internal quality defects in bricks and tiles.

[0103] In one embodiment, feature extraction of the preprocessed signal also includes a signal broadening coefficient;

[0104] It's important to note that the signal broadening factor refers to the degree of spectral expansion of an ultrasonic signal during propagation due to uneven interfaces, poor probe contact, or differences in the physical properties of bricks and tiles. When ultrasonic waves pass through the interface of bricks and tiles, if the interface is not smooth or the contact is incomplete, the sound waves will scatter and diffract during propagation, resulting in a broadened time-domain waveform. A larger signal broadening factor indicates a higher degree of energy diffusion, suggesting poor contact between the probe and the brick surface, preventing normal signal propagation and affecting detection accuracy. A large signal broadening factor is usually an indicator of poor probe contact, meaning that the ultrasonic signal loses some energy during reflection and propagation at the interface, potentially leading to the failure to detect actual internal defects in the bricks and tiles or misidentification of them as defects. Therefore, analyzing the signal broadening factor can effectively determine whether the ultrasonic probe is in good contact with the brick surface, avoiding misjudgments caused by poor contact.

[0105] Specifically, the calculation steps for the signal broadening factor are as follows:

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

[0107] The full width at half maximum (FWHM) of the envelope is calculated using the formula: FWHM = t2 - t1; where t1 and t2 are the start and end times when the signal envelope drops to half its maximum value, respectively.

[0108] The duration RH of the signal envelope, i.e., the total time length of the signal envelope from the start point to the end point, is calculated using the formula: RH = t end -t start , t end and t start These are the start and end times of the envelope signal, respectively.

[0109] The formula for calculating the signal broadening factor is as follows: In the formula, BN is the signal broadening coefficient.

[0110] It's important to note that the primary purpose of envelope extraction using the Hilbert transform is to extract the instantaneous amplitude (i.e., envelope) of the original signal, effectively reflecting the change in signal strength over time. In ultrasonic signal analysis, envelope extraction eliminates the influence of high-frequency components, focusing on energy changes in the signal, thus making the signal broadening characteristics more apparent and accurate. Using the Hilbert transform, the non-stationarity of the signal can be better captured, especially during signal broadening; changes in the envelope can help reveal signal attenuation and expansion caused by interface irregularities, poor contact, etc. Calculating the signal broadening coefficient in this way not only improves detection accuracy but also reduces the interference of noise and high-frequency components on the results.

[0111] In one implementation, analyzing the signal broadening coefficient is beneficial for determining whether poor contact between the probe and the brick surface leads to misjudgment of internal defects in the bricks and tiles. By analyzing the signal broadening degree, signal scattering and diffraction phenomena caused by uneven interfaces, incomplete probe contact, etc., can be identified. A large signal broadening coefficient indicates that the ultrasonic signal has experienced significant energy loss and waveform distortion during propagation, which is usually a sign of poor contact between the probe and the brick / tile surface. If the contact is poor, the signal cannot be accurately transmitted and reflected, which may lead to misjudgment of internal defects in the bricks and tiles or complete failure to detect potential problems. By analyzing the signal broadening coefficient, misjudgments caused by poor contact can be effectively eliminated, ensuring more accurate detection results, thereby improving the reliability of brick and tile quality inspection, avoiding missed or false detections, and ensuring that the detection results reflect the true quality condition of the bricks and tiles.

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

[0113] The frequency offset coefficient refers to the degree to which the frequency of an ultrasonic signal shifts during propagation due to poor contact between the probe and the brick surface, uneven interface, or differences in the physical properties of the brick materials. When ultrasonic waves pass through the brick-tile interface, poor contact or an uneven interface can cause reflection and scattering of the sound waves during propagation, resulting in a frequency shift. A larger frequency offset coefficient indicates a more significant change in the frequency of the ultrasonic signal, usually indicating 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, making the frequency offset phenomenon more pronounced. This may affect the accuracy and quality of the signal, and consequently, the judgment of internal defects in the bricks and tiles. Therefore, by analyzing the frequency offset coefficient, the quality of the probe-brick surface contact can be effectively judged, thereby ensuring the accuracy of the test results and avoiding misjudgments or missed detections due to poor contact.

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

[0115] Perform a Fast Fourier Transform on the target signal to convert it to the frequency domain, obtaining the spectrum S(f); where f is the frequency.

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

[0117]

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

[0119] Based on the center frequency f0 and the preset ideal frequency f d The frequency offset Δf is calculated using the formula: Δf = f0 - f d The frequency offset coefficient is calculated based on the frequency offset Δf, using the following formula: 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 makes good contact with the brick surface and there are no other interfering factors. This frequency is usually determined through experimental calibration or based on theoretical models, and represents the expected frequency of the signal under normal propagation conditions. When the ultrasonic signal propagates without interference, the signal frequency should be close to this ideal value. If the frequency deviates, it may indicate poor contact between the probe and the brick surface, or the presence of other factors affecting propagation. Therefore, the preset ideal frequency provides a benchmark for judging the probe contact status and signal quality; the specific preset ideal frequency is set by professionals according to the actual situation, and will not be limited or elaborated upon here.

[0121] In one implementation, analyzing the frequency offset coefficient is beneficial for determining whether poor contact between the probe and the brick surface leads to misjudgment of internal defects in bricks and tiles. The frequency offset coefficient reflects the degree of frequency variation in the ultrasonic signal. Under ideal propagation conditions, the frequency of an ultrasonic signal should be close to the preset ideal frequency. If the frequency offset coefficient is large, it indicates that the signal propagation has been abnormally affected, possibly due to incomplete contact between the probe and the brick surface or an uneven interface, resulting in scattering or attenuation during signal propagation. This frequency offset not only affects the quality of the ultrasonic signal but may also lead to misjudgment or missed detection of internal defects, further impacting the accuracy of brick and tile quality inspection. By analyzing the frequency offset coefficient, poor contact can be identified in a timely manner, avoiding misjudgments caused by poor contact, thereby improving the reliability and accuracy of the inspection.

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

[0123]

[0124] In the formula, DFR is the contact state coefficient, ZX, BN and CX are the energy loss coefficient, signal broadening coefficient and frequency offset coefficient respectively, and 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.

[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, and 0.3 respectively, or other numbers. There are no specific restrictions.

[0126] In one embodiment, the step of comparing the contact state coefficient with a preset contact state coefficient threshold and determining whether the contact between the probe and the brick / tile surface is qualified based on the comparison result is as follows:

[0127] The contact state coefficient is compared 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 indicates that the contact between the probe and the brick surface is unqualified. An alarm will be issued and the sound wave signal will be 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 based on the actual situation, and no specific limitations or details are provided.

[0130] It should be noted that by comparing the contact state coefficient with a preset contact state coefficient threshold, the contact quality between the ultrasonic probe and the brick / tile surface can be effectively determined. When the contact state coefficient is less than the preset threshold, it indicates good contact between the probe and the brick / tile surface, allowing the ultrasonic signal to propagate smoothly and resulting in reliable test results. However, if the contact state coefficient does not meet the preset standard, it indicates poor contact between the probe and the brick / tile surface, which may lead to signal reflection or attenuation, thus affecting the accuracy of the test. Therefore, the system will issue an alarm and request a retransmission of the acoustic signal until the contact state coefficient returns to a qualified level, ensuring the reliability and accuracy of the test. This process effectively avoids misjudgments and missed detections caused by poor contact, guaranteeing the accuracy of brick / tile quality testing.

[0131] In one embodiment, when the contact between the probe and the brick / tile surface is qualified, the defect characteristics in the target signal are analyzed to determine whether the brick / tile has internal defects. The steps for quality inspection of the brick / tile are as follows:

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

[0133] The target signal is divided into multiple segments so that each segment can be analyzed separately.

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

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

[0136] Calculating energy entropy: Using the probability distribution of energy, energy entropy is calculated. The formula for energy entropy is: In the formula, HNK is the energy entropy, p j This represents the energy percentage of the j-th signal segment, where M is the total number of signal segments;

[0137] The energy entropy and maximum amplitude of the target signal are normalized, and the internal defect coefficient is obtained based on the normalized energy entropy and maximum amplitude of the 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, then there is a defect inside the brick; otherwise, there is no defect.

[0138] It's important to note that energy entropy is a measure of the uncertainty of information in a signal; it reflects the distribution of signal energy. A higher energy entropy indicates a more complex energy distribution, typically caused by inhomogeneities or defects (such as cracks, pores, and loose areas) within the brick or tile. These defects alter the sound wave propagation path, causing scattering and reflection during propagation, thus generating more complex components in both the frequency and time domains of the signal. As the severity of the defects increases, more stray components appear in the signal, and the energy entropy also increases. Therefore, a higher energy entropy is often an indicator of internal defects and can help determine the quality of the brick or tile.

[0139] It's important to note that the maximum amplitude value refers to the maximum amplitude of the signal, representing its intensity. The presence of defects can increase signal reflection, thus raising the maximum value. A larger maximum amplitude value indicates a stronger signal, typically due to reflection or scattering of ultrasonic signals when they encounter obstacles or inhomogeneous media (such as cracks, pores, or other defects) during propagation, leading to increased signal reflection intensity. Therefore, a large maximum amplitude value may indicate the presence of defects within the brick or tile, resulting in increased signal reflection or diffraction. The presence of defects often alters the propagation path and reflection characteristics of sound waves, leading to a higher received signal amplitude. Therefore, analyzing the maximum amplitude value of the signal can effectively determine the likelihood of internal defects in the brick or tile.

[0140] It should be noted that the calculation steps for normalizing the energy entropy and maximum amplitude value of the target signal, and then 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, and c1 and c2 are the preset ratio 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 based on 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. There are no specific restrictions. In addition, the preset internal defect coefficient threshold is set by professionals based on the actual situation. There are no specific restrictions or details.

[0142] In one implementation, a laser is first emitted onto the surface of the red brick tile to scan it. The strength and phase of the reflected signal are used to determine if there are any quality problems on the surface. If no quality problems are found on the surface, ultrasonic waves are emitted to further determine if there are any internal quality problems. Compared to image-based quality detection, this laser scanning and ultrasonic testing method has significant advantages. First, laser scanning can accurately acquire detailed information about the brick tile surface, determining surface flatness by the strength and phase of the reflected signal, avoiding the influence of factors such as lighting, angle, and surface reflection that can affect traditional image detection. Second, ultrasonic technology can penetrate deep into the brick tile to detect potential defects beneath the surface, such as cracks and voids, which are difficult to identify with image detection. Furthermore, the combination of laser and ultrasonic waves makes the brick tile quality inspection process more comprehensive, ensuring both surface quality and high-precision assessment of internal defects, thereby improving the overall accuracy and reliability of the inspection.

[0143] Based on the same inventive concept, this invention also provides a quality inspection system for bricks and tiles. See also Figure 2 , Figure 2 A framework diagram of a quality inspection system for bricks and tiles provided in an embodiment of the present invention is shown. The system includes:

[0144] The uneven reflection intensity module scans the surface of red bricks and tiles by emitting a laser and calculating the uneven reflection intensity coefficient based on the strength of the reflected signal; it evaluates whether the distribution of reflected signals on the brick and tile surface is uniform.

[0145] Phase anomaly change module: acquires the phase of the reflected signal and calculates the phase anomaly change coefficient based on the phase of the reflected signal; evaluates the abnormal fluctuation of the phase of the reflected signal on the brick and tile surface;

[0146] Quality inspection module: Based on the reflection intensity non-uniformity coefficient and phase abnormal change coefficient, the surface quality defect coefficient is obtained, and the presence of quality problems on the surface of red bricks and tiles is determined based on the surface quality defect coefficient. According to the embodiment of the present invention, a quality inspection system for bricks and tiles is provided. Through the above method, high-precision and comprehensive quality inspection of bricks and tiles can be achieved, reducing the occurrence of false detection or missed detection.

[0147] The foregoing has provided a detailed description of one embodiment of the present invention, but this description is merely a preferred embodiment and should not be construed as limiting the scope of the invention. All equivalent variations and modifications made within the scope of the present invention should still fall within the patent coverage of the present invention.

Claims

1. A method for quality detection of tiles, characterized in that, The method comprises the following steps: The surface quality defect coefficient is obtained according to the reflection intensity uneven coefficient and the phase abnormal change coefficient, and whether the red brick tile surface has a quality problem is judged according to the surface quality defect coefficient. The reflection intensity uneven coefficient and the phase abnormal change coefficient are calculated as follows: Laser is emitted to the brick tile surface, and the reflected signal is received; according to different positions of the scanning area, the reflection intensity values of the corresponding positions are extracted; The mean value and the standard deviation of all reflection intensity values are calculated, and the standard deviation is divided by the mean value to obtain the reflection intensity uneven coefficient. Laser is emitted to the brick tile surface, and the reflected signal is received; according to different positions of the scanning area, the phase values of the corresponding positions of the reflection signal are extracted; The mean value of all phase values of the reflection signal is calculated, the absolute difference value between each phase value of the reflection signal and the mean value is calculated, and the sum of all absolute difference values is calculated to obtain the phase abnormal change coefficient. The surface quality defect coefficient is obtained according to the reflection intensity uneven coefficient and the phase abnormal change coefficient, and whether the red brick tile surface has a quality problem is judged according to the surface quality defect coefficient. The surface quality defect coefficient is compared with a preset surface quality defect coefficient threshold value; if the surface quality defect coefficient is not less than the preset surface quality defect coefficient threshold value, it indicates that the red brick tile surface has a quality problem, and a first-level alarm is issued; If the surface quality defect coefficient is less than the preset surface quality defect coefficient threshold value, it indicates that the red brick tile surface does not have a quality problem, and further analysis is required to determine whether there is a defect inside the brick tile. wherein, is a surface quality defect coefficient, and are a reflection intensity unevenness coefficient and a phase abnormality change coefficient, respectively, are respectively and a preset proportion value, and are all greater than 0; and the sum of the and is 1. When the red brick tile surface does not have a quality problem, whether there is a quality problem inside the red brick tile is further determined by emitting ultrasonic waves to the red brick tile, and the specific steps are as follows: After the detection light emitted by the ultrasonic probe penetrates the brick tile, the sound wave signal is received by the other end probe, and the received sound wave signal is preprocessed and normalized to obtain a target signal; 2. A method for quality detection of tiles according to claim 1, characterized in that, Feature extraction is performed on the target signal, including an energy loss coefficient, a signal widening coefficient and a frequency shift coefficient, and a contact state coefficient is obtained according to the energy loss coefficient, the signal widening coefficient and the frequency shift coefficient; The contact state coefficient is compared with a preset contact state coefficient threshold value, and whether the contact between the probe and the brick tile surface is qualified is judged according to the comparison result; When the contact between the probe and the brick tile surface is qualified, the defect characteristics in the target signal are analyzed to determine whether there is an internal defect in the brick tile, and the quality of the brick tile is detected. The calculation steps of the energy loss coefficient are as follows: The calculation steps of the signal widening coefficient are as follows: The envelope of the target signal is extracted by Hilbert transform to obtain the envelope of the target signal. The ultrasonic signal emitted by the probe is recorded as an original signal, and the duration of the original signal emission is obtained, and the total energy of the input ultrasonic signal is calculated, and the formula is: , wherein, is the total energy of the input ultrasonic signal, is the duration, represents the instantaneous amplitude of the ultrasonic signal emitted by the probe; The target signal received by the other end probe is acquired, and the total energy of the target signal is calculated by analyzing and calculating the target signal, and the formula is: , wherein, is the total energy of the received ultrasonic signal, is the duration, represents the instantaneous amplitude of the target signal; Computing the energy loss coefficient The formula for the computation is: where, is the energy loss coefficient; The calculation steps of the frequency shift coefficient are as follows: The contact state coefficient is obtained according to the energy loss coefficient, the signal widening coefficient and the frequency shift coefficient. Full width half maximum of the envelope is calculated The formula for the calculation is: ; and are the start and end times respectively when the signal envelope falls to half of the maximum value. Duration of the signal envelope is calculated The formula for the duration of the signal envelope is calculated as: , and are the start time and end time of the envelope signal, respectively. The signal spread factor is calculated according to the formula: , wherein is the signal spread factor; ​ performing a fast Fourier transform on the target signal to transform the target signal into a frequency domain to obtain a frequency spectrum ; is a frequency; Center frequency of a computed signal spectrum The formula for the computation is wherein, is the power density of the spectrum, representing the energy distribution of the signal in the frequency domain; According to the center frequency and the preset ideal frequency Calculate the frequency offset , the formula is: According to the frequency offset Calculate the frequency offset coefficient, the formula is: , wherein, The frequency offset coefficient; ​ wherein, is a contact state coefficient, , and are an energy loss coefficient, a signal broadening coefficient and a frequency shift coefficient, respectively, are preset proportion values of , and , and are all greater than 0; and the sum of is 1. The step of judging whether the contact between the probe and the brick surface is qualified according to the comparison result is: Comparing the contact state coefficient with a preset contact state coefficient threshold value, if the contact state coefficient is less than the preset contact state coefficient threshold value, it indicates that the contact between the probe and the brick surface is qualified; If the contact state coefficient is not less than the preset contact state coefficient threshold value, it indicates that the contact between the probe and the brick 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 value.

3. A method for quality detection of tiles according to claim 2, characterized in that, When the contact between the probe and the brick surface is qualified, the defect characteristics in the target signal are analyzed to judge whether the brick has internal defects, and the step of quality detection of the brick is: The defect characteristics in the target signal include energy entropy and maximum amplitude value; The target signal is divided into multiple small segments for separate analysis of each segment; The energy of each segment is calculated: for each segment, the energy thereof is calculated; The energy is calculated in the form of average value of signal amplitude square; The energy of each segment is normalized to obtain the probability distribution of energy, i.e. the proportion of the energy of each segment in the total energy; The formula for calculating energy entropy is: In the formula, For energy entropy, Indicates the first The energy percentage of the segment signal It is the total number of signal segments; The energy entropy and the maximum amplitude value of the target signal are normalized, and an internal defect coefficient is obtained according to the normalized energy entropy and the maximum amplitude value of the target signal, the internal defect coefficient is compared with a preset internal defect coefficient threshold value, if the internal defect coefficient is not less than the preset internal defect coefficient threshold value, the brick has internal defects; otherwise, it does not.

4. A quality detection system for tiles for implementing a quality detection method for tiles according to any one of claims 1 to 3, characterized in that, The system comprises: A reflection intensity unevenness module: the surface of the red brick is scanned by emitting laser to the surface of the red brick, and a reflection intensity unevenness coefficient is calculated according to the strength of the reflection signal; whether the distribution of the reflection signal of the brick surface is uniform is evaluated; A phase abnormal change module: the phase of the reflection signal is obtained, and a phase abnormal change coefficient is calculated according to the phase of the reflection signal; the abnormal fluctuation of the phase of the reflection signal of the brick surface is evaluated; A quality detection module: a surface quality defect coefficient is obtained according to the reflection intensity unevenness coefficient and the phase abnormal change coefficient, and whether the red brick surface has quality problems is judged according to the surface quality defect coefficient.

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