Earthen ruins bottom surface disease prediction method based on intelligent sensing and infrared image technology

Abstract

The invention discloses an earthen ruin bottom surface disease prediction method based on intelligent sensing and infrared image technologies, and the method comprises the following steps: S1, obtaining an infrared image of the bottom of an earthen ruin through a bottom surface infrared sensing image obtaining system, and forming a capillary water rising height change curve based on the infrared image; s2, the basic humidity monitoring sensing system collects humidity, temperature and salinity data of the basic position of the ruins; s3, drawing a relation curve of humidity, temperature, salinity and time of the basic position of the ruin, then establishing a relation curve of the average inflection point value, humidity, salinity and time of the surface position of the ruin, further obtaining basic curve characteristics of alkali efflorescence and biological diseases of the surface position of the earthen ruin, and according to the shape and the change trend of the basic curve characteristics, calculating the biological diseases of the surface position of the earthen ruin. And a disease characteristic curve database is formed, so that the earthen archaeological site disease development trend is pre-judged and monitored. The saltpetering and biological disease evolution database improves the scientificity of ruins surface disease analysis, provides a large amount of data and basis for finding and reducing earthen ruins surface diseases, and avoids the phenomenon that the diseases are discussed by experts purely through experience to give a conclusion.

Description

Technical Field

[0001] The present invention belongs to the technical field of cultural relics protection, and specifically relates to the control of surface diseases at the bottom of earthen ruins, and in particular to a method for predicting surface diseases at the bottom of earthen ruins based on intelligent sensing and infrared imaging technology. Background Art

[0002] Earthen sites are the difficulty and focus of the protection of various cultural relics. With the warming of the climate and the increase in rainfall, especially the increase in extreme rainfall, the annual change of groundwater level has increased. Earthen sites are usually located on a low ground, which makes it easy for water to accumulate around them. The strength of the earthen sites is low and the water properties are poor. Under the combined action of rainwater and groundwater, earthen sites often experience alkali reversion, shedding and microbial diseases. These diseases do not change significantly on the surface before exposure, but after exposure, the disease takes a long time to occur and causes significant damage to the surface. Due to insufficient understanding of water migration and current technical limitations, the cultural relics community believes that water-induced alkali reversion and biological diseases are the difficulties in cultural relics protection research.

[0003] With the development of electronic technology and image technology, human beings' understanding of natural phenomena has entered the era of wireless perception and image (optical and infrared) cognitive phenomena from the era of "eyes" and "human brain" memory to the era of information and intelligence. The understanding of natural phenomena has entered the era of data from the surface phenomenon, which has prompted the development of cultural relics protection technology from the era of experience to the era of rationality. Rational understanding depends on the collection of data and the recognition of laws. Obtaining data on alkali return and biological diseases in earthen sites has become a hot spot and key to cultural relics protection. Many scholars have tried to establish the intrinsic connection between the reflectance of visible-near infrared spectrum and the properties of samples such as moisture and salt. However, the soil moisture prediction model is difficult to apply to the determination of surface moisture content in earthen sites; some scholars have also tried to use neural network method to establish a hyperspectral inversion soil moisture model, but the model has many variables, low model operation efficiency, poor stability and poor practicality. Some scholars have also used infrared cameras to detect temperature changes on the surface of earthen sites, and tried to use infrared images to discover the impact of water on alkali reversion and biological diseases in earthen sites. However, the images of current infrared detection equipment are easily affected by the external environment (temperature, light), and the test structure is only effective when the water content of cultural relics is relatively high. The results are highly biased and the workload is large, and the actual effect of solving the problem is poor. It can be seen that a single technology cannot solve the prediction of surface diseases at the bottom of earthen sites. It is an inevitable trend for the scientific and standardized protection of earthen sites to fully consider the principle of indestructible soil bodies in earthen sites and establish a fast and reliable method for predicting surface diseases at the bottom of earthen sites.

[0004] To this end, we proposed a method for predicting surface diseases at the bottom of earthen sites based on intelligent sensing and infrared imaging technology to provide guidance for the prevention of alkali reversion and biological diseases in ancient buildings. Summary of the invention

[0005] In view of the current situation that the recognition, evaluation and prediction of existing earthen site surface diseases such as alkali reversion are still at the qualitative evaluation level of the "eye", based on intelligent sensing and infrared imaging technology, through real-time monitoring of earthen site foundation humidity, real-time monitoring of infrared images of the bottom surface of earthen sites, calculation of image humidity eigenvalues ​​and other methods, a database of bottom surface alkali reversion and biological disease evolution and a disease prediction system with the humidity characteristic curve of disease evolution as key indicators are established, in order to solve the arbitrariness of existing earthen site surface disease evaluation and the blindness of disease treatment. The present invention provides a method for predicting earthen site bottom surface diseases based on intelligent sensing and infrared imaging technology.

[0006] To achieve the purpose of the invention, the technical solution adopted by the present invention is as follows: To achieve the above purpose, the specific technical solution adopted by the present invention is as follows: A method for predicting surface damage at the bottom of earthen ruins based on intelligent sensing and infrared imaging technology comprises the following steps: S1. Obtain an infrared image of the bottom of the site using a bottom surface infrared sensor image acquisition system, and form a capillary water rise height variation curve based on the infrared image; S2, the basic humidity monitoring sensor system collects humidity, temperature, and salinity data at the basic location of the site; S3. Draw the relationship curve between humidity, temperature, salinity and time at the base of the site, and then establish the average inflection point value, humidity, salinity and time relationship curve at the surface of the site based on the temperature in the infrared image, and then derive the basic curve characteristics of alkali return and biological diseases at the surface of the earthen site. According to the shape and change trend of the basic curve characteristics, a disease characteristic curve database is formed to predict and monitor the development trend of earthen site diseases.

[0007] Among them, the basic curve characteristics have obvious inflection points, indicating that the moisture content of the earthen site is high and changes dramatically in the inflection point area, which is prone to water migration and evaporation of water on the surface of the site, thereby causing surface cracking and salt accumulation and other diseases. According to the shape and change trend of the inflection point value curve before and after the occurrence of alkali return and biological diseases, a disease characteristic curve database is formed to predict and monitor the development trend of earthen site diseases. Furthermore, the specific steps of obtaining an infrared image of the bottom of the ruins by using the bottom surface infrared sensor image acquisition system and forming a curve of the capillary water rise height based on the infrared image are as follows: S101, firstly, perform an upper boundary analysis on the temperature data matrix of the infrared image at the bottom of the ruins: select the temperature data of the infrared image of the area above the upper boundary, and perform mean calculation on the temperature data; S102, using a power function to transform the temperature matrix data, and enhancing the change of the upper boundary data; S103, converting the temperature data matrix processed by the power function into an enhanced infrared image, and determining the height of the capillary water rise in the form of an image; S104, selecting multiple positions in the middle area of ​​the image, drawing multiple temperature curves from bottom to top, recording the inflection point of each temperature curve, and calculating the average inflection point value; S105 , obtaining average inflection point values ​​of infrared images at different times, drawing a curve of the relationship between the average inflection point value and time, and forming a curve of the change of the capillary water rising height based on the infrared image.

[0008] Furthermore, the temperature data of the area below the height of 10-20 cm above the upper boundary is selected as the analysis object.

[0009] Furthermore, the power function is used to transform the temperature data matrix and enhance the change of the upper boundary data: Divide the original temperature data matrix by the average temperature Get the normalized matrix, define the power function exponent n, select the range between 2-4, and construct the power function formula (1) The power function is used to transform the data of the uniform matrix to enhance the changes in the upper boundary data.

[0010] Furthermore, when collecting infrared images of the bottom of the ruins, the pan / tilt first moves the infrared camera to the image collection position. After a delay of 1 second, the industrial computer turns on the infrared camera and takes an infrared image. The infrared image data is then fed back to the processor of the data processing system to obtain the temperature data of the infrared image.

[0011] Furthermore, the specific process of step S3 is as follows: firstly, according to the data of the positions of different measuring points of the basic humidity monitoring sensor system, a relationship curve between humidity, temperature, salinity and time is drawn; Secondly, establish the data of the relationship between the average inflection point value of temperature, humidity, salinity and time, and draw the curve of the relationship between the average inflection point value of temperature, humidity, salinity and time; Finally, the curve changing trends of the average temperature inflection point value, humidity, salinity and time and their mutual relationships are analyzed to obtain the correlation index between the surface temperature and basic humidity, and the basic curve characteristics of the average temperature inflection point value, humidity, salinity and time corresponding to the alkali return and biological diseases on the surface of the earthen site are obtained, so as to predict and monitor the development trend of earthen site diseases and take precautions against diseases in advance.

[0012] Specifically, for a certain point in the earthen site, the humidity change curve of the point can be drawn according to the relationship between infrared images and temperature and humidity, and the inflection point value in the curve of each day can be found. The inflection point values ​​of each day are concentrated together to obtain the inflection point change curve. Then, according to the change of salt content on the surface of the earthen site and the progress of surface weathering, the basic curve characteristics of alkali return and biological diseases on the surface of the earthen site can be summarized. Such a curve with obvious inflection points indicates that the moisture content of the earthen site is high and changes drastically in the inflection point area, which is easy to cause water migration and evaporation of water on the surface of the site, thereby causing surface cracking and salt accumulation and other diseases. According to the shape and change trend of the inflection point value curve before and after the occurrence of alkali return and biological diseases, a database of characteristic curves for generating diseases is formed, and then the development trend of earthen site diseases is predicted and monitored. A prediction method for the bottom surface disease of earthen sites based on intelligent sensing and infrared image technology is established, and measures are taken in advance to control the change amplitude of the surface moisture of the earthen site and reduce the inflection point value of the characteristic curve, providing a basis for the protection of earthen sites and guidance for preventive protection.

[0013] Furthermore, basic humidity monitoring sensors are arranged within a range of 0.5-2 meters below the ground around the earthen site, and an array method is adopted, and one or more sensors can be arranged at one point from top to bottom.

[0014] Among them, the following devices are used to implement the above method, including a soil site foundation humidity monitoring sensor system, a bottom surface infrared sensor image acquisition system, an infrared image processing system, and a database of alkali return and biological disease evolution; The basic humidity monitoring sensor system is used to collect the change value of basic humidity caused by the change of groundwater level in real time; The bottom surface infrared sensing image acquisition system is used to collect infrared images of the bottom surface of the earthen ruins in real time; The infrared image processing system is used to enhance the temperature difference value of the infrared image and obtain the characteristic value of the surface temperature at the bottom of the ruins; The alkali reversion and biological disease evolution database is used to obtain indicators such as changes in the surface temperature of earthen sites, surface temperature change curves, and the correlation between surface temperature and basic humidity, thereby forming a method for predicting alkali reversion and biological diseases.

[0015] The basic humidity monitoring sensor system includes a sensor device, data acquisition software and a laptop computer. The sensor device has a wifi function and can collect humidity, temperature, salinity and other functions; the acquisition software has the functions of storing data and displaying real-time data curves.

[0016] The bottom surface infrared sensing image acquisition system includes an infrared image acquisition camera, image acquisition software and a laptop computer. The infrared image acquisition instrument has a wifi function and has the functions of scaling, rotating, transmitting and image data conversion. When performing fixed-point data acquisition and transmission, the pan-tilt head first moves the infrared camera to the image acquisition position, and after a delay of 1 second, the industrial computer turns on the infrared camera and takes an infrared image, and then feeds the image data back to the processor of the data processing system.

[0017] Beneficial technical effects of the invention: (1) The present invention performs enhanced analysis based on the temperature field distribution and change differences in the infrared image, avoids various interferences caused by the external environment, and accurately extracts the temperature distribution and change rules in the captured infrared image; it has the characteristics of simplicity, efficiency and high accuracy, adopts intelligent sensing and infrared imaging technology, does not require contact testing, is simpler than contact testing, and adopts wireless data transmission instead of contact testing, which improves the efficiency and scope of the test. In particular, infrared imaging technology improves the scope and efficiency of disease identification.

[0018] (2) The basic forward-looking monitoring data improves the pertinence of subsequent infrared image monitoring. According to the law and migration path of capillary water transfer, the changes in humidity and salinity of the sensors at the base are the prerequisites for the subsequent changes in humidity and temperature on the surface of the earthen site. When the temperature and humidity sensor data suddenly increase, the frequency of infrared image monitoring of changes on the surface of the site should be increased to timely detect changes in moisture on the surface of the earthen site.

[0019] (3) The database on alkali reversion and biological disease evolution has improved the scientific nature of the analysis of surface diseases at sites, provided a large amount of data and basis for the discovery and reduction of surface diseases at earthen sites, and avoided the phenomenon in which experts simply draw conclusions based on experience.

[0020] (4) The image enhancement technology is used to improve the accuracy of detecting the capillary water rise boundary. The infrared image of the enhanced data formed makes it easier to detect the height of the capillary water rise, thereby improving the accuracy and visibility of recognition. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 Schematic diagram of data acquisition equipment layout; Figure 2 Flow chart of the method for predicting surface damage at the bottom of earthen ruins; Figure 3 Infrared image and temperature distribution diagram of the bottom of the site; Figure 4 (a) is the basic humidity change curve. Figure 4 (b) is the curve of humidity change on the surface of the earthen site; Figure 5 Schematic diagram of inflection point change; Note: 1 Earthen site; 2 Upper foundation of aquifer; 3 Lower foundation of aquifer; 4 Infrared image acquisition camera; 5 Sensor; 6 Upper boundary line; 7 Average inflection point value. DETAILED DESCRIPTION

[0022] The present invention is further described below in conjunction with specific implementation methods. The accompanying drawings are only used for exemplary descriptions and are only schematic diagrams, not actual drawings, and cannot be understood as limiting this patent; in order to better illustrate the embodiments of the present invention, some parts of the accompanying drawings may be omitted, enlarged or reduced, and do not represent the size of the actual product; for those skilled in the art, it is understandable that some well-known structures and their descriptions in the accompanying drawings may be omitted.

[0023] In order to make the objectives, technical solutions and advantages of the present invention more clear, the present invention will be further described below in conjunction with the accompanying drawings.

[0024] The earthen ruins of Kaifeng city wall are used as monitoring objects, and annual inspection is carried out. A disease prediction device is set on the bottom surface of the earthen ruins 1, such as Figure 1 As shown, it includes an earthen site 1, an infrared sensor image acquisition system arranged on the bottom surface of the earthen site 1, an infrared image processing system, and an alkali reversion and biological disease evolution database. The foundation of the earthen site 1 is divided into an upper aquifer foundation 2 and a lower aquifer foundation 3. There is an underground water level in the lower aquifer foundation 3. Humidity monitoring sensor systems are arranged on the upper aquifer foundation 2 and the lower aquifer foundation 3.

[0025] The basic humidity monitoring sensor system is used to collect the change value of basic humidity caused by the change of groundwater level in real time; The bottom surface infrared sensing image acquisition system is used to collect infrared images of the bottom surface of the earthen ruins in real time; The infrared image processing system is used to enhance the temperature difference value of the infrared image and obtain the characteristic value of the surface temperature at the bottom of the ruins; The alkali reversion and biological disease evolution database is used to obtain indicators such as the change of surface temperature of earthen sites, the surface temperature change curve, the correlation between surface temperature and basic humidity, and form a prediction method for alkali reversion and biological diseases; The basic humidity monitoring sensor system includes sensor 5, data acquisition software and a laptop computer. The sensor device has a wifi function and can collect humidity, temperature, salinity and other functions; the acquisition software has the function of storing data and displaying real-time data curves.

[0026] The sensors 5 are arranged within 0.5-2 meters below the ground around the earthen site 1, usually in an array method, and one or more sensors can be arranged from top to bottom at one point. The sensors are connected to the data acquisition, and the data acquisition instrument transmits and stores data with the notebook via wifi.

[0027] The bottom surface infrared sensing image acquisition system includes an infrared image acquisition camera 4, image acquisition software and a laptop computer. The infrared image acquisition camera 4 has a wifi function and has the functions of zooming, rotating, transmitting and image data conversion. When performing fixed-point data acquisition and transmission, the pan-tilt head first moves the infrared image acquisition camera to the image acquisition position, and after a delay of 1s, the industrial computer turns on the infrared image acquisition camera and takes an infrared image, and then feeds the image data back to the processor of the data processing system.

[0028] The infrared image processing system performs upper boundary 6 (i.e., the highest boundary of capillary water rise) analysis on the temperature data matrix of the infrared image, with the goal of highlighting the upper boundary 6 of the temperature change.

[0029] A method for predicting the bottom surface damage of earthen ruins based on intelligent sensing and infrared imaging technology. Figure 2 As shown, the following steps are included: S1. Obtain an infrared image of the bottom of the site using the bottom surface infrared sensor image acquisition system, and form a curve of the capillary water rise height based on the infrared image: S101 selects the temperature data of the infrared image above the upper boundary 6 and below the height of 10-20cm, calculates the data matrix through the python program, and automatically calculates the mean of the temperature data to obtain the average temperature ; S102, dividing the original temperature matrix by the average temperature Get the normalized matrix, define the power function exponent n, usually in the range of 2-4, and construct the power function formula (1) The power function is used to transform the data of the homogenized matrix to enhance the change of the upper boundary data; S103, converting the uniform matrix processed by the power function into an enhanced infrared image, and determining the height of the capillary water rise in the form of an image; S104, selecting multiple positions in the middle area of ​​the image, drawing multiple temperature curves from bottom to top, recording the inflection point of each temperature curve, and calculating the average inflection point value; S105, obtaining the average inflection point value 7 of the infrared image at different times, drawing a curve of the relationship between the average inflection point value 7 and time, and forming a curve of the change of the capillary water rising height based on the infrared image.

[0030] S2. The basic humidity monitoring sensor system collects humidity, temperature and salinity data at the basic location of the site.

[0031] S301. First, based on the data from the basic humidity monitoring sensor system, the humidity, temperature, and salinity data are sorted out. The infrared image and temperature distribution diagram of the bottom of the site are as follows: Figure 3 As shown in the figure, according to the location of different measuring points, the relationship curve between humidity, temperature, salinity and time at the base of the site is drawn, see Figure 4 ; S302. Next, establish data on the relationship between the average inflection point value, humidity, salinity and time, and draw a curve of the relationship between the average inflection point value, humidity, salinity and time. Figure 5 ; S303. Finally, the curve variation trend of the average inflection point value, humidity, salinity and time and their mutual relationship are analyzed, such as Figure 5 As shown, each point in the curve comes from Figure 4 (b) Inflection point in the curve: For a certain point in the earthen site, we can draw a daily humidity change curve for that point based on the infrared image and the relationship between temperature and humidity, and find the inflection point value in the curve every day. Then, we can gather the inflection point values ​​of each day together and draw a Figure 5 The basic curve characteristics of alkali return and biological diseases on the surface of earthen sites can be summarized according to the changes in salt content and surface weathering progress of the earthen sites, such as Figure 5 The characteristic curve of the disease shown in the figure has a curve with a clear inflection point, indicating that the moisture content of the earthen site is high and changes dramatically in the inflection point area, which is prone to water migration and evaporation of water on the surface of the site, thereby causing surface cracking and salt accumulation and other diseases. According to the shape and change trend of the inflection point value curve before and after the occurrence of alkali return and biological diseases, a disease characteristic curve database is formed to predict the development trend of earthen site diseases, establish a prediction method for the bottom surface of earthen sites based on intelligent sensing and infrared imaging technology, take measures in advance, control the change range of surface moisture in earthen sites, reduce the inflection point value of the characteristic curve, and provide a basis for the protection of earthen sites and guidance for preventive protection.

[0032] Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field and related fields without creative work should fall within the scope of protection of the present invention. The structures, devices and operating methods not specifically described and explained in the present invention are implemented according to the conventional means in the field unless otherwise specified and limited.

Claims

1. A method for predicting surface damage at the bottom of earthen ruins based on intelligent sensing and infrared imaging technology, characterized in that: The following steps are involved: S1. Obtain an infrared image of the bottom of the site using a bottom surface infrared sensor image acquisition system, and form a capillary water rise height variation curve based on the infrared image; S2, the basic humidity monitoring sensor system collects humidity, temperature, and salinity data at the basic location of the site; S3. Draw the relationship curve between humidity, temperature, salinity and time at the base of the site, and then establish the relationship curve between the average inflection point value, humidity, salinity and time at the surface of the site, and then obtain the basic curve characteristics of alkali return and biological diseases at the surface of the earthen site. According to the shape and change trend of the basic curve characteristics, a disease characteristic curve database is formed to predict and monitor the development trend of earthen site diseases.

2. The method for predicting surface damage at the bottom of earthen ruins according to claim 1, characterized in that: The specific steps of obtaining an infrared image of the bottom of the ruins by using the bottom surface infrared sensor image acquisition system and forming a capillary water rise height variation curve based on the infrared image are as follows: S101 first performs an upper boundary analysis on the temperature data matrix of the infrared image at the bottom of the ruins: selects the temperature data of the infrared image of the area above the upper boundary and calculates the mean of the temperature data; S102 uses a power function to transform the temperature matrix data and enhance the change of the upper boundary data; S103 converts the temperature data matrix processed by the power function into an enhanced infrared image, and determines the height of the capillary water rise in the form of an image; S104: selecting multiple positions in the middle area of ​​the image, drawing multiple temperature curves from bottom to top, recording the inflection point of each temperature curve, and calculating the average inflection point value; S105 obtains average inflection point values ​​of infrared images at different times, draws a curve of the relationship between the average inflection point value and time, and forms a curve of the change of the capillary water rising height based on the infrared image.

3. The method for predicting surface damage at the bottom of earthen ruins according to claim 2, characterized in that: The temperature data of the area below the height of 10-20 cm above the upper boundary were selected as the analysis object.

4. The method for predicting surface damage at the bottom of earthen ruins according to claim 3, characterized in that: The power function is used to transform the temperature data matrix and enhance the change of the upper boundary data: Divide the original temperature data matrix by the average temperature Get the normalized matrix, define the power function exponent n, select the range between 2-4, and construct the power function formula (1) The power function is used to transform the data of the uniform matrix to enhance the changes in the upper boundary data.

5. The method for predicting surface damage at the bottom of earthen ruins according to claim 2, characterized in that: When collecting infrared images of the bottom of the ruins, the pan / tilt first moves the infrared camera to the image collection position. After a delay of 1 second, the industrial computer turns on the infrared camera and takes an infrared image. The infrared image data is then fed back to the processor of the data processing system to obtain the temperature data of the infrared image.

6. The method for predicting surface damage at the bottom of earthen ruins according to claim 1 or 4, characterized in that: The specific process of step S3 is: firstly, according to the data of the positions of different measuring points of the basic humidity monitoring sensor system, a relationship curve between humidity, temperature, salinity and time is drawn; Secondly, establish the data of the relationship between the average inflection point value of temperature, humidity, salinity and time, and draw the curve of the relationship between the average inflection point value of temperature, humidity, salinity and time; Finally, the curve changing trends of the average temperature inflection point value, humidity, salinity and time and their mutual relationships were analyzed to obtain the correlation index between the surface temperature and basic humidity, and the basic curve characteristics of the average temperature inflection point value, humidity, salinity and time corresponding to the alkali return and biological diseases on the surface of the earthen site were obtained, so as to predict and monitor the development trend of earthen site diseases.

7. The method for predicting surface damage at the bottom of earthen ruins according to claim 6, characterized in that: The basic humidity monitoring sensors are arranged within the range of 0.5-2 meters below the ground around the earthen site. An array method is adopted, and one or more sensors can be arranged at one point from top to bottom.

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