Disclosure of Invention
In order to solve the problems, the invention provides a defective product detection method and system for high-temperature heat-insulating brick production.
On one hand, the defective product detection system for producing the high-temperature heat insulation bricks provided by the invention comprises the following components:
The detection module comprises a laser heat conduction instrument and an infrared camera, and is configured to perform periodic heat wave heating on the brick body to be detected through the laser heat conduction instrument, and then record temperature data of the brick body to be detected through the infrared camera, so as to calculate the thermal diffusivity;
the heating determining module is connected with the detecting module and is configured to acquire the thickness of the brick body to be detected, and determine the pulse width, the period duration and the heating power of the periodic heat wave heating according to the thickness of the brick body;
the heating adjustment module is respectively connected with the detection module and the heating determination module and is configured to adjust the heating power in the periodic heat wave heating process according to the ambient temperature;
And the evaluation module is configured to calculate an evaluation value of the brick body to be tested according to the number ratio of the processing points to the suspected defect points.
Further, the detection module is configured to, when the laser heat conduction instrument is used for periodically heating the brick to be detected, include:
Periodically heating the brick body to be detected in a square wave pulse heating mode, selecting a plurality of points on the surface of the brick body to be detected as processing points, wherein the processing points are points with known position coordinates, acquiring temperature data of the processing points and corresponding data acquisition time, and acquiring the thermal diffusivity through the following relation:
;
Wherein,In order to achieve a thermal diffusivity, the thermal diffusivity,To address the distance of the point from the heat source,>0,In order to heat the signal frequency,Indicating the phase lag.
Further, when judging whether a defect area exists in the brick body to be tested according to the thermal diffusivity, the method comprises the following steps:
Taking the data acquisition time as an abscissa and the thermal diffusivity corresponding to the data acquisition time on the same processing point as an ordinate, establishing a processing point diffusivity change curve, and calculating the slope of the diffusivity change curve;
Under the condition of selecting the same data acquisition time, slope sets are established for slopes of different processing points, and the average value and standard deviation of the slope sets are calculated;
defining a slope threshold according to the average and standard deviation, wherein the slope threshold meets the following relation:
;
Wherein,As a slope threshold value,As an average value of the values,Is the standard deviation of the two-dimensional image,Is the slope sensitivity coefficient which is less than or equal to 1≤3;
And acquiring position coordinates corresponding to slopes which are not in the slope threshold, marking the position coordinates as suspected defect points, and determining a defect area according to the suspected defect points.
Further, determining the defect region from the suspected defect point includes:
Analyzing the suspected defect points one by one, taking the suspected defect points as target points one by one, acquiring position coordinates of the rest suspected defect points in a circular range of a radius R, calculating an average value of the horizontal coordinates and an average value of the vertical coordinates of the position coordinates of the rest suspected defect points except the target points when the number of adjacent or continuous suspected defect points exceeds a number threshold, calculating distance values of the point and a circle center by taking the average value of the horizontal coordinates and the average value of the vertical coordinates as the horizontal coordinates and the vertical coordinates respectively, selecting a minimum distance value when analyzing the suspected defect points one by one, and determining a circular range corresponding to the minimum distance value as a defect area.
Further, the number threshold satisfies the following relationship:
;
Wherein,As a function of the number of threshold values,To average the number of suspected defect points in the circular range for a standard brick at the same data acquisition time,Is the number sensitivity coefficient which is less than or equal to 2≤3,Is the standard deviation of suspected defect points of a standard brick body in a circular range under the same data acquisition time.
Further, determining the pulse width, the period duration and the heating power of the periodic heat wave heating according to the thickness of the brick body comprises the following steps of respectively calculating and obtaining the pulse width, the period duration and the heating power according to the following relation:
;
;
;
Wherein,In order to be a pulse width,The thickness of the brick body is equal to the thickness of the brick body,For the duration of the period of time,To design coefficient, 2< ><3,In order to be able to heat the power,Is the density of the brick body, and the density of the brick body is the density of the brick body,For the preset target temperature rise,For the area of the heated region,Is the specific heat capacity of the brick body to be measured.
Further, when the heating power in the periodic heat wave heating process is adjusted according to the ambient temperature, the method comprises the steps of obtaining the ambient temperature and the target temperature of the brick body, wherein the adjusted heating power meets the following relation:
;
Wherein,In order to adjust the heating power after the adjustment,In order to be at the temperature of the environment,Is the target temperature of the brick body.
Further, calculating an evaluation value of the brick to be tested according to the number ratio of the processing points to the suspected defect points, including:
Judging whether a defect area exists or not, and if the defect area does not exist, acquiring a calculated evaluation value by the following method:
;
Wherein,In order to evaluate the score value,In order to handle the number of points of interest,Is the number of suspected defect points.
Further, if the defect area exists, judging the brick to be tested as a defective product.
Compared with the prior art, the invention has the beneficial effects that:
The traditional high-temperature heat-insulating brick detection method mainly relies on appearance detection, and can not effectively evaluate the thermal performance and internal defects of the brick body. According to the scheme, the laser heat conduction instrument is combined with the infrared camera, and the thermal diffusivity of the brick body is obtained in a periodic thermal wave heating mode, so that the heat conduction performance inside the brick body can be directly reflected. By calculating the thermal diffusivity change curves at different positions, potential defect areas in the brick body are identified, and false detection or missing detection caused by appearance judgment only is avoided.
The existing detection method mostly adopts manual spot check, has low detection efficiency and subjectivity, and laboratory tests generally need long-time sampling, preparation and analysis, so that the method is difficult to adapt to mass production. According to the scheme, the heating parameters are automatically calculated through the heating determining module, so that proper detection conditions can be obtained for different bricks, the heating power is compensated in real time through the heating adjusting module, the influence of environmental factors (such as room temperature change) on detection accuracy is eliminated, the quality of the bricks is scored through the evaluating module, manual intervention is reduced, and the detection flow is more intelligent.
The traditional detection method generally needs to be adjusted for different brick specifications, the scheme obtains the thickness of the brick through the heating determination module, dynamically calculates the pulse width, the period duration and the heating power of periodic heat wave heating, can adapt to the bricks with different thicknesses and sizes, and adopts an automatic compensation algorithm to adjust the heating power according to the change of the environmental temperature so as to ensure the detection consistency, so that the method can be applied to various production environments.
Conventional thermal detection methods generally rely on visual changes in the temperature field, and cannot accurately quantify defects. According to the scheme, a data-driven defect identification model is established by calculating a slope set of thermal diffusivity, a slope threshold is defined through a statistical method (average value and standard deviation), high-precision defect positioning is achieved, a spatial clustering algorithm is adopted, thermal diffusivity data of a brick body are combined, distribution of suspected defect points is analyzed, a defect area is accurately defined, and misjudgment is avoided.
The system can not only identify defective products, but also calculate the quality scores of the brick bodies through the evaluation module, if the defective products are defective, calculate the scores according to the uniformity of the thermal diffusivity of the brick bodies, ensure the refinement and grading of the product quality, and if the defective products are detected, the system can rapidly judge the defective products, prevent the defective products from entering the market, and improve the reliability of quality control.
The traditional laboratory test mode generally needs a long detection period, and the scheme adopts a non-contact real-time detection mode, can directly perform online detection, improves the production efficiency, reduces the heat energy loss in the subsequent kiln use by accurately identifying defective bricks, and reduces the energy waste caused by using low-quality heat insulation bricks.
On the other hand, the invention also provides a defective product detection method for producing the high-temperature heat-insulating brick, which comprises the following steps:
The method comprises the steps of carrying out periodic heat wave heating on a brick body to be tested through a laser heat conduction instrument, recording temperature data of the brick body to be tested through an infrared camera, and calculating thermal diffusivity;
acquiring the thickness of a brick body to be tested, and determining the pulse width, the period duration and the heating power of periodic heat wave heating according to the thickness of the brick body;
adjusting the heating power in the periodic heat wave heating process according to the ambient temperature;
and after judging that the defect area exists, evaluating the score of the brick to be tested according to the defect area, and judging that the brick to be tested is a defective product when the score is smaller than or equal to the minimum score.
It can be appreciated that the above-mentioned defective product detection method for high-temperature insulating brick production has the same beneficial effects as the system thereof, and will not be described herein.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art. It should be noted that, without conflict, the embodiments of the present application and features of the embodiments may be combined with each other. The application will be described in detail below with reference to the drawings in connection with embodiments.
Referring to fig. 1, this embodiment provides a defective product detection system for high-temperature insulating brick production, including:
The detection module comprises a laser heat conduction instrument and an infrared camera, is configured to perform periodic heat wave heating on the brick body to be detected through the laser heat conduction instrument, and then records temperature data of the brick body to be detected through the infrared camera to calculate the thermal diffusivity;
The heating determining module is connected with the detecting module and is configured to acquire the thickness of the brick body to be detected, and the pulse width, the period duration and the heating power of the periodic heat wave heating are determined according to the thickness of the brick body;
the heating adjustment module is respectively connected with the detection module and the heating determination module and is configured to adjust heating power in the periodic heating process according to the ambient temperature;
And the evaluation module is configured to calculate an evaluation value of the brick body to be tested according to the number ratio of the processing points to the suspected defect points.
It should be noted that, with laser heat conduction appearance and infrared camera, obtain the thermal diffusivity of the brick body through periodic heat wave heating, can nondestructive test brick body internal defect, avoid only relying on the erroneous judgement and the omission that outward appearance detection caused, improve the accuracy of detection. The heating determining module automatically adjusts pulse width, period duration and heating power according to the thickness of the brick body, ensures that the brick bodies with different thicknesses can be properly heated and detected, and improves the adaptability and universal applicability of the system. The traditional method is greatly influenced by the fluctuation of the ambient temperature, and the heating power in the periodic heating process is dynamically adjusted through the heating adjustment module, so that the stability of detection conditions is ensured, and the reliability and repeatability of detection are improved. The evaluation module can not only identify defective products, but also grade the brick body according to the defective areas, so that finer quality control is realized, and resource waste caused by misjudgment is avoided. By adopting non-contact type heat wave heating and infrared detection, automatic online detection can be realized, the inefficiency of traditional manual spot check is avoided, the method is suitable for mass production, and the production line efficiency is improved. The intelligent detection system reduces manual intervention, reduces the possibility of human misjudgment, simultaneously eliminates defective products accurately, reduces rejection rate, improves material utilization rate, and accords with the green manufacturing concept.
In some embodiments of the present application, the detection module is configured to, when periodically heating the brick to be tested by the laser thermal conductivity meter, include:
Periodically heating the brick body to be measured in a square wave pulse heating mode, selecting a plurality of points on the surface of the brick body to be measured as processing points, wherein the processing points are points with known position coordinates, acquiring temperature data of the processing points and corresponding data acquisition time, and acquiring the thermal diffusivity through the following relationship:
;
Wherein,In order to achieve a thermal diffusivity, the thermal diffusivity,To address the distance of the point from the heat source,>0,In order to heat the signal frequency,Indicating the phase lag.
When a plurality of points on the surface of the brick to be tested are selected as processing points, specifically, as many points as possible in a circular area are selected as the processing points, and the number of the processing points can be determined according to the processing capacity of the equipment or the system.
Phase Lag (Phase Lag), also known as Phase delay, is the time delay of an output signal relative to an input signal in a periodic wave system. Phase lag refers to the delay between the phase of the change in the temperature of the brick surface and the change in the heating source (e.g., a pulsed heat source) during the propagation of the thermal wave.
The phase lag data acquisition mode is that an infrared camera is adopted to record the temperature change T (T) of the brick surface along with time. The periodically heated input signal Q (t) is acquired by data acquisition. Fourier transforming the input heating signal Q (t) to obtain the phase of the dominant frequency component fQ. Fourier transforming the temperature response signal T (T) to obtain the phase of the dominant frequency componentT。
The phase lag is calculated according to the following relationship:。
Here, theQ is the phase of the heating signal,T is the phase of the temperature response, typically in radians (rad) or degrees (°).
In the thermal wave analysis, the thermal wave propagates in a sine wave manner, and thus the change in the thermal wave can be described using the linear frequency f or the angular frequency ω. When the angular frequency omega is used for calculation, the corresponding thermal diffusivity formula is brought into omega instead of 2pi f, so that the following form is obtained:
。
According to the technical scheme provided by the embodiment, the laser heat conduction instrument is used for periodically heating the brick body to be tested, and the square wave pulse heating mode is utilized, so that periodic thermal excitation can be uniformly applied to the brick body in a short time. Compared with the traditional continuous heating method, the method can generate temperature gradient faster, so that the temperature response of internal defects is more obvious, and the sensitivity of defect detection is improved.
In the data acquisition process, the embodiment selects a plurality of processing points on the surface of the brick body, wherein the processing points are all known position coordinates, so that the temperature change characteristics can be accurately analyzed. Especially, the method selects as many points as possible in the circular area as processing points, so that the data acquisition quantity can be maximized under the same heating condition, the spatial resolution of detection is improved, and the detection result of the defects is more accurate. Because the number of processing points can be flexibly adjusted according to the processing capacity of the system, the optimal balance between the detection precision and the calculation efficiency can be achieved.
In the scheme of the embodiment, whether defects exist in the brick body or not is judged by calculating the thermal diffusivity. Thermal diffusivity is an important indicator of the heat conducting capacity of a material, and if defects (such as pores, cracks or impurities) exist in the brick body, the thermal diffusivity usually shows abnormal changes. Compared with the traditional surface temperature detection method, the method can more directly represent the integrity of the internal structure of the brick body by calculating the thermal diffusivity, thereby realizing more accurate defect detection.
In the detection process, the scheme introduces Phase Lag (Phase Lag) calculation, wherein the Phase Lag is a key parameter in the process of periodic thermal wave propagation, and can effectively reflect the thermal response characteristic of the brick body. Because of the time dependence of the thermal diffusion process, when the heating source periodically acts on the brick surface, the temperature response will be delayed from the input heating signal, which is the phase lag. The scheme extracts the phase information of the main frequency component through Fourier transformation, thereby calculating the phase difference delta between the heating signal and the temperature response signal. The calculation method can remove the influence of environmental noise and aperiodic disturbance, improves the robustness of detection, and ensures that the calculation of the thermal diffusivity is more stable and reliable.
In this embodiment, the temperature signal T (T) and the input heating signal Q (T) are analyzed by using a fourier transform, and compared with the conventional time domain analysis method, the fourier transform can decompose the signal into components with different frequencies, so that the detection is more accurate and efficient. By extracting the phase information of the main frequency component, the interference of external temperature fluctuation can be eliminated, and the stability and repeatability of detection are ensured. Meanwhile, as the Fourier transform can highlight the characteristic of the periodic signal, high-precision defect detection can be still realized under lower heating power, the energy consumption is reduced, and the system efficiency is improved.
In addition, the scheme of the embodiment has high automation capability in data processing, and can realize automatic identification and classification of defects, reduce manual intervention and improve detection efficiency through steps of real-time data acquisition, fourier transform analysis, phase lag calculation and the like. Traditional manual detection or laboratory detection methods generally require a long time to perform data analysis, and the detection system of the embodiment can rapidly complete detection on a production line, so that the production efficiency is greatly improved.
In some embodiments of the present application, when judging whether a defect area exists in the inside of the brick body to be measured according to the thermal diffusivity, the method includes:
taking the data acquisition time as an abscissa and the thermal diffusivity of the corresponding data acquisition time on the same processing point as an ordinate, establishing a processing point diffusivity change curve, and calculating the slope of the diffusivity change curve;
Under the condition of selecting the same data acquisition time, slope sets are established for slopes of different processing points, and the average value and standard deviation of the slope sets are calculated;
defining a slope threshold according to the average value and the standard deviation, wherein the slope threshold meets the following relation:
;
Wherein,As a slope threshold value,As an average value of the values,Is the standard deviation of the two-dimensional image,Is the slope sensitivity coefficient which is less than or equal to 1≤3;
And acquiring position coordinates corresponding to all slopes which are not in the slope threshold, marking the position coordinates as suspected defect points, and determining a defect area according to the suspected defect points.
It should be noted that, in this embodiment, by analyzing the trend of thermal diffusivity over time, a diffusivity variation curve is established and its slope is calculated, so as to accurately characterize the thermal conductivity inside the brick body. Compared with the method for judging by directly using the absolute value of the thermal diffusivity, the method has the advantages that local anomalies can be more sensitively identified by utilizing the slope change trend, and the defect detection accuracy is improved.
In the embodiment, a multi-point data comparison analysis method is adopted, slope values of different processing points are extracted under the same data acquisition time, a slope set is established, and the average value and the standard deviation of the slope set are calculated. The method can effectively reduce the influence caused by single-point measurement errors and improve the stability and reliability of detection.
By defining the slope threshold, the embodiment can adapt to the characteristic changes of different brick materials. The calculation mode of the slope threshold combines the average value and the standard deviation and introduces a slope sensitivity coefficient(1≤Not more than 3), the system can be flexibly adjusted according to different detection requirements, so that the sensitivity of defect detection can be enhanced, and misjudgment can be avoided.
In this embodiment, the points exceeding the slope threshold are screened, the corresponding position coordinates are marked as suspected defect points, and the defect area is further analyzed. Compared with the traditional single-point abnormality judgment mode, the method can provide more complete defect form information, so that the boundary identification of the defect area is more accurate, and the defect positioning accuracy is improved.
In some embodiments of the present application, determining a defective area from suspected defective points includes:
and analyzing the suspected defect points one by one, taking the suspected defect points as target points one by one, acquiring position coordinates of the rest suspected defect points in a circular range of a radius R, calculating an abscissa mean value and an ordinate mean value of the position coordinates of the rest suspected defect points except the target points when the number of adjacent or continuous suspected defect points exceeds a number threshold, calculating distance values between the points and a circle center by taking the abscissa mean value and the ordinate mean value as the abscissas and the ordinatordinates respectively, selecting a minimum distance value when analyzing the suspected defect points one by one, and determining a circular range corresponding to the minimum distance value as a defect area.
According to the historical data, the lengths of cracks of the brick body are counted, and the radius R is the average value of the lengths of the cracks in the historical data/2.
In the "when the number of adjacent or continuous suspected defective points exceeds the number threshold", the adjacent condition means that the number of surrounding suspected defective points exceeds the number threshold with the analyzed suspected defective point (target point) as the center, and the continuous condition means that the number of defective points on a straight line or curve including the target point exceeds the number threshold, and the "exceeding" means a relationship of greater than (excluding equal to).
In some embodiments of the application, the quantity threshold satisfies the following relationship:
;
Wherein,As a function of the number of threshold values,To average the number of suspected defect points in the circular range for a standard brick at the same data acquisition time,Is the number sensitivity coefficient which is less than or equal to 2≤3,Is the standard deviation of suspected defect points of a standard brick body in a circular range under the same data acquisition time.
It can be understood that, in this embodiment, by performing local cluster analysis on the suspected defect points, it is ensured that the determination of the defect area is more accurate and scientific. The conventional method is generally used for judging defects only based on a single abnormal point, but the embodiment can effectively avoid misjudgment caused by measurement errors or local abnormality by statistically analyzing the spatial distribution of a plurality of suspected defect points, and improve the reliability of defect identification.
In this embodiment, a circular region clustering method is adopted, that is, each suspected defect point is taken as a center, and other suspected defect points within the radius R range are examined. The R is selected according to the average value of the crack length of the brick body in the historical data, the design ensures that the judgment of the defect area accords with the actual physical characteristics of the brick body, the threshold value is not set at will, and the scientificity and the adaptability of defect identification are enhanced.
In the case of performing defect region determination, the present embodiment focuses not only on the number of adjacent suspected defective points but also on the distribution characteristics thereof. By analyzing whether a defect point (namely the possible extending direction of the crack) exists on a continuous straight line or curve, the abnormal local dispersion point and the real defect area can be more accurately distinguished, and the precision of crack detection is improved.
According to the embodiment, a calculation method of the quantity threshold is introduced, statistical data of standard brick bodies under the same heating detection condition is utilized, and the setting of the quantity threshold can be adapted to the production conditions of different brick bodies by combining an average value, a standard deviation and a quantity sensitivity coefficient (m is more than or equal to 2 and less than or equal to 3). Compared with a mode of fixing a threshold value, the method is more adaptive, can be dynamically adjusted according to the material characteristics and the heat conduction characteristics of different brick bodies, and improves the generalization capability of the system.
In some embodiments of the application, determining the pulse width, the period duration and the heating power of the periodic heat wave heating according to the thickness of the brick body comprises the following steps of respectively calculating and obtaining the pulse width, the period duration and the heating power according to the following relation:
;
;
;
Wherein,In order to be a pulse width,The thickness of the brick body is equal to the thickness of the brick body,For the duration of the period of time,To design coefficient, 2< ><3,In order to be able to heat the power,Is the density of the brick body, and the density of the brick body is the density of the brick body,For the preset target temperature rise,For the area of the heated region,Is the specific heat capacity of the brick body to be measured.
It should be noted that, according to the embodiment, the periodic heating process of the thermal wave is optimized through the dynamic heating parameter adjustment based on the thickness of the brick body, so that the brick bodies with different thicknesses can obtain proper heat input, and the accuracy and the stability of detection are improved.
In the process of heating by pulse heat waves, the pulse width is%) The device is positively correlated with the thickness (d) of the brick body, so that heat can be effectively transferred into the brick body, and the detection accuracy is not affected by insufficient energy caused by too short pulse or surface overheating caused by too long pulse. The design coefficient is adopted for adjustment, so that the pulse width is suitable for the characteristics of different brick materials, and the applicability of the method is improved.
The present embodiment optimizes the heating cycle duration (T) at the same time, the setting of which depends also on the brick thickness (d) and on a design factor. Therefore, enough heating and cooling cycles can be completed within a reasonable time range, and the influence of heat accumulation on subsequent data acquisition is prevented, so that the change of a temperature curve can reflect the internal defect condition of the brick body more.
For calculation of heating power (P), the density (ρ), target temperature rise (DeltaT) and heated area (A) of the brick body are fully considered, so that the input energy is ensured to be matched with the thermophysical property of the brick body, and the condition of insufficient heating or excessive heating is avoided. Compared with a method for fixing heating power, the method can dynamically adjust power according to physical characteristics of the brick body, so that calculation of thermal diffusivity is more stable, and reliability of detection results is improved.
Overall, this embodiment has optimized pulse width, cycle duration and heating power through the heating parameter self-adaptation adjustment based on brick thickness for detecting system can adapt to the high temperature insulating brick of different specifications and materials, has improved defect detection's precision and application scope, has promoted the intelligent level of system.
The design factor gamma is obtained by the experiment that the first step in determining the design factor is to obtain the thermophysical properties of the brick. Under laboratory conditions, basic parameters of the brick body are measured, including density, specific heat capacity and thermal conductivity of the brick body. These parameters determine the heat spreading capacity of the brick and affect the time and intensity required for heating. Especially when the thickness of the brick body is large, the heat diffusion speed is relatively slow, so that the heating time needs to be properly prolonged, and the design coefficient also needs to be correspondingly adjusted.
The second step is to conduct experimental tests. In the initial stage, different design coefficients can be selected, and the temperature change of the surface of the brick body can be observed in the actual detection process. The dynamic distribution condition of the temperature is recorded through the infrared camera, whether the heating process is uniform or not is analyzed, and meanwhile the temperature is ensured not to be too high or too low. The test mode may include gradually adjusting the design factor with a fixed pulse heating time and observing the temperature profile, and then continuing to adjust the design factor with a fixed cycle length to ensure that the thermal diffusion achieves the desired effect.
The third step is data analysis and optimization. Experimental data under different design coefficients are collected, statistical analysis is carried out, and the temperature distribution, heating uniformity and defect identification accuracy of the brick body under different design coefficients are compared. A data fitting method may be used, for example, by comparing temperature variations under different conditions, to determine which design coefficients are most stable for the heating process, and to effectively identify defective areas. In addition, error analysis may be introduced, such as calculating a deviation value of the target temperature and the actual measured temperature, or calculating an accuracy of defect detection, to select an optimal design coefficient.
The fourth step is to build an empirical formula. Based on experimental data, the relation between the design coefficient, the thickness of the brick body and the heat diffusion capacity can be generalized. For example, as the thickness of the brick increases, the design factor typically needs to be increased appropriately to compensate for the longer heat diffusion time, and if the thermal conductivity of the brick is stronger, the design factor may be decreased appropriately to prevent temperature changes from affecting measurement accuracy too quickly. Through the comparative analysis of a large amount of experimental data, the value range of the design coefficient can be finally determined, and a calculation rule is established, so that the detection requirements of different bricks can be automatically met.
And finally, determining a final design coefficient and verifying in practical application. Multiple tests can be performed with standard bricks to ensure that selected design coefficients remain stable under different test conditions. If the heating effect is not good under some special conditions in the application process, the value range of the design coefficient can be further adjusted, so that the design coefficient can be more accurately adapted to different brick materials and thicknesses.
In some embodiments of the present application, when adjusting the heating power in the periodic heating process according to the ambient temperature, the method includes obtaining the ambient temperature and the target temperature of the brick body, where the adjusted heating power satisfies the following relationship:
;
Wherein,In order to adjust the heating power after the adjustment,In order to be at the temperature of the environment,Is the target temperature of the brick body.
In some embodiments of the present application, calculating an evaluation value of a brick to be tested according to a number ratio of a processing point to a suspected defect point includes:
Judging whether a defect area exists or not, and if the defect area does not exist, acquiring a calculated evaluation value by the following method:
;
Wherein,In order to evaluate the score value,In order to handle the number of points of interest,Is the number of suspected defect points.
It should be noted that, in this embodiment, the heating process is more stable and accurate by compensating the heating power with the ambient temperature, so as to improve the reliability of defect detection. The ambient temperature can affect the initial temperature of the brick body, which in turn affects the accuracy of the calculation of the thermal diffusivity. Therefore, by correcting the heating power P', the embodiment ensures that the brick body can reach a reasonable target temperature under different environmental conditions, and avoids erroneous judgment caused by environmental temperature deviation. The adjustment formula adopts a linear correction mode, so that the temperature difference influence can be effectively corrected, and the calculation is kept simple and efficient, thereby enhancing the adaptability of the system and enabling the system to stably operate under different climatic conditions.
In terms of defect evaluation, the embodiment provides a scoring mechanism based on a slope threshold value, and the quality of the brick body is evaluated by counting the number of effective points in the slope circle threshold value. The formula of Score fully considers the uniformity of the thermal diffusivity of the brick surface, and the scoring range is 0-100%, so that the detection result can not only distinguish qualified products from unqualified products, but also provide finer quality grade division. The method can effectively reflect the severity of brick defects, help the production process to carry out classified screening, and improve the accuracy of quality control.
The scoring method is robust in that it relies not only on single point data, but is based on overall statistics of multiple processing points so that even if individual error points exist, overall assessment results are not affected. In addition, the setting of the scoring standard can adapt to different types of brick detection, so that the universality of the detection system is enhanced.
In a combined view, the two improvement points of the embodiment ensure the detection stability through the ambient temperature compensation on one hand, and provide more visual quality evaluation standards through a scoring mechanism on the other hand, so that the intelligent level and the practical application value of the system are improved as a whole.
In some embodiments of the present application, if there is a defective area, the brick to be tested is determined to be defective.
Referring to fig. 2, the embodiment provides a defective product detection method for producing a high-temperature insulating brick, which includes:
S1, periodically heating a brick body to be tested by using a laser heat conduction instrument, recording temperature data of the brick body to be tested by using an infrared camera, and calculating thermal diffusivity;
S2, obtaining the thickness of a brick body to be tested, and determining the pulse width, the period duration and the heating power of periodic heat wave heating according to the thickness of the brick body;
S3, adjusting the heating power in the periodic heat wave heating process according to the ambient temperature;
And S4, calculating the evaluation value of the brick to be tested according to the number ratio of the processing points to the suspected defect points.
It should be noted that, first, the method realizes non-contact detection of internal defects of the brick body by combining a laser heat conduction instrument and an infrared camera. Compared with the traditional destructive detection method, the method can accurately acquire the heat diffusion characteristic of the brick body on the premise of not affecting the integrity of the brick body, so that whether internal defects exist or not is judged, the detection efficiency is improved, and meanwhile, the waste of materials is avoided.
Secondly, the method adaptively adjusts the pulse width, the period duration and the heating power of the periodic heat wave heating according to the thickness of the brick body, so that the brick bodies with different thicknesses can be reasonably heated. The adjusting mechanism can effectively improve the adaptability of detection, is suitable for the production of heat insulation bricks with different specifications, and is beneficial to improving the universality of the system.
In addition, the method further combines the ambient temperature to dynamically adjust the heating power, and can effectively reduce the influence of the ambient temperature change on the detection precision. In the actual production environment, temperature fluctuation may cause detection errors, and by means of adjusting heating power, the heating stability of the brick body can be ensured, so that the detection accuracy and consistency are improved.
Finally, the method ensures the objectivity of defect judgment by quantifying the evaluation value. When the defect exists in the brick body, the system can calculate specific scores and judge defective products according to the set minimum score threshold. The scoring mechanism can effectively reduce errors of human judgment, improve consistency and reliability of detection, and simultaneously provide more accurate data support for quality control.
Finally, it should be noted that the above embodiments are only for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the above embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made to the specific embodiments of the present invention without departing from the spirit and scope of the present invention, and any modifications and equivalents are intended to be included in the scope of the claims of the present invention.