A water conservancy project building anti-seepage quality monitoring equipment

Abstract

The present invention relates to the technical field of permeability detection, and in particular to a water conservancy project building anti-seepage quality monitoring device. Firstly, based on the fluctuation of the temperature monitoring value in each monitoring area monitored by an infrared thermal imager, the temperature anomaly degree of each monitoring area is determined; further, according to the humidity monitoring data in each monitoring area and the leakage possibility determined by the bubble distribution, the credibility of the temperature anomaly degree of each monitoring area is characterized, so as to measure the anti-seepage quality evaluation coefficient more accurately in combination with the temperature anomaly degree and the leakage possibility, so that the anti-seepage quality monitoring of the water conservancy project building can be carried out more accurately according to the anti-seepage quality evaluation coefficient.

Description

Technical Field

[0001] The invention relates to the technical field of permeability detection, and in particular to a water conservancy engineering building anti-seepage quality monitoring device. Background Art

[0002] Water conservancy engineering buildings such as dams, dikes, underground reservoirs and other facilities play a vital role in anti-seepage treatment. The purpose of anti-seepage design is to prevent water leakage and protect the stability and service life of the structure. The quality of the anti-seepage layer directly affects the safety and economy of water conservancy projects. Therefore, effective quality monitoring and maintenance are crucial.

[0003] In the prior art, the method for monitoring the anti-seepage quality of water conservancy project buildings usually adopts infrared thermal imaging. However, the response of infrared thermal imaging to temperature changes may be delayed, resulting in certain monitoring errors in the real-time monitored thermal imaging data, thereby affecting the accuracy of the anti-seepage quality assessment of water conservancy project buildings. That is, the accuracy of the prior art using infrared thermal imaging to monitor the anti-seepage quality of water conservancy project buildings is poor. Summary of the invention

[0004] The present application provides a device for monitoring the anti-seepage quality of water conservancy engineering buildings. The device first determines the degree of temperature anomaly in each monitoring area based on the fluctuation of the temperature monitoring value in each monitoring area monitored by an infrared thermal imager; further, the degree of temperature anomaly in each monitoring area is characterized for credibility according to the humidity monitoring data in each monitoring area and the leakage possibility determined by the bubble distribution, so as to measure the anti-seepage quality evaluation coefficient more accurately in combination with the degree of temperature anomaly and the leakage possibility, thereby solving the problem that the infrared thermal imaging method may have a delayed response to temperature changes, resulting in certain monitoring errors in the thermal imaging data monitored in real time, affecting the accuracy of the anti-seepage quality evaluation of water conservancy engineering buildings, so that more accurate anti-seepage quality monitoring of water conservancy engineering buildings can be carried out according to the anti-seepage quality evaluation coefficient.

[0005] The present application provides a water conservancy project building anti-seepage quality monitoring device, including a monitoring data integration center, an ultrasonic hygrometer, an infrared thermal imager and an image collector; the ultrasonic hygrometer is used to collect humidity monitoring data; the infrared thermal imager is used to collect temperature monitoring values; the image collector is used to collect surface images of monitoring areas; the ultrasonic hygrometer, the infrared thermal imager and the image collector are all connected to the monitoring data integration center by signals; the monitoring data integration center obtains humidity monitoring data in each monitoring area on the surface of the water conservancy project building, the number of surface bubbles and the temperature monitoring value at each monitoring point position according to the humidity monitoring data collected by the ultrasonic hygrometer, the temperature monitoring value collected by the infrared thermal imager and the surface image of the monitoring area collected by the image collector;

[0006] Determine the temperature distribution disorder of each monitoring area according to the fluctuation of the temperature monitoring values ​​at each monitoring point in each monitoring area; determine the temperature anomaly degree of each monitoring area according to the temperature distribution disorder and the prominence of the temperature distribution disorder of each monitoring area relative to other monitoring areas;

[0007] Determine the possibility of leakage in each monitoring area according to the humidity monitoring data, the number of bubbles on the surface, and the deviation of the humidity monitoring data of each monitoring area relative to the humidity monitoring data of other monitoring areas;

[0008] The anti-seepage quality assessment coefficient of each monitoring area is determined according to the temperature anomaly degree and the leakage possibility; and the anti-seepage quality monitoring of the water conservancy project building is carried out according to the anti-seepage quality assessment coefficient.

[0009] Furthermore, the process of obtaining the temperature distribution disorder includes:

[0010] Calculate the variance and range of the temperature monitoring values ​​at all monitoring points in each monitoring area;

[0011] The temperature distribution disorder of each monitoring area is determined according to the temperature monitoring value variance and the temperature monitoring value range; the temperature monitoring value variance and the temperature monitoring value range are both positively correlated with the temperature distribution disorder.

[0012] Further, determining the temperature distribution disorder of each monitoring area according to the temperature monitoring value variance and the temperature monitoring value range includes:

[0013] The temperature distribution disorder of each monitoring area is determined according to the product of the temperature monitoring value variance and the temperature monitoring value range.

[0014] Furthermore, the process of obtaining the temperature anomaly degree includes:

[0015] Taking each monitoring area as a target area in turn, and taking other monitoring areas outside the target area as corresponding reference areas;

[0016] Determining the reference temperature distribution deviation of each reference area according to the difference between the temperature distribution disorder of the target area and the temperature distribution disorder of each corresponding reference area;

[0017] The temperature anomaly degree of the target area is determined according to the temperature distribution disorder of the target area and the overall size of the reference temperature distribution deviation of each corresponding reference area.

[0018] Further, determining the temperature anomaly degree of the target area according to the overall size of the reference temperature distribution deviations of the reference areas corresponding to the target area includes:

[0019] The product of the mean value of the reference temperature distribution deviations of all reference areas corresponding to the target area and the temperature distribution disorder of the target area is taken as the temperature anomaly degree of the target area.

[0020] Furthermore, the process of obtaining the leakage possibility includes:

[0021] Calculate the difference in humidity monitoring data between each monitoring area and each other monitoring area; take the mean of all humidity monitoring data differences corresponding to each monitoring area as the reference humidity distribution deviation of each monitoring area;

[0022] The leakage possibility of each monitoring area is determined based on the humidity monitoring data, reference humidity distribution deviation and surface bubble number of each monitoring area; the humidity monitoring data, reference humidity distribution deviation and surface bubble number are all positively correlated with the leakage possibility.

[0023] Further, determining the leakage possibility of each monitoring area according to the humidity monitoring data of each monitoring area, the reference humidity distribution deviation and the number of surface bubbles includes:

[0024] The product of the humidity monitoring data, the reference humidity distribution deviation and the number of surface bubbles in each monitoring area was normalized to determine the leakage possibility of each monitoring area.

[0025] Furthermore, the process of obtaining the anti-seepage quality assessment coefficient includes:

[0026] The product of the temperature anomaly degree and the leakage possibility is normalized by negative correlation to determine the anti-seepage quality assessment coefficient of each monitoring area.

[0027] Furthermore, the monitoring of the anti-seepage quality of water conservancy engineering buildings according to the anti-seepage quality assessment coefficient includes:

[0028] The monitoring areas whose anti-seepage quality assessment coefficient is less than the preset assessment threshold are judged as areas with unqualified anti-seepage quality of water conservancy project buildings and are marked by jet marking equipment.

[0029] Furthermore, the preset evaluation threshold is set to 0.57.

[0030] This application has the following beneficial effects:

[0031] For each monitoring area on the surface of a water conservancy project building, its surface will be covered with an anti-seepage layer, and the surface of the anti-seepage layer shows a uniform temperature distribution; therefore, when the anti-seepage layer on the surface of the monitoring area is unevenly applied or there is water penetration, the corresponding temperature distribution will be uneven, that is, chaotic; therefore, this application first determines the degree of temperature distribution chaos in each monitoring area based on the fluctuation of the temperature monitoring value at each monitoring point in each monitoring area. In addition, since the anti-seepage layer on the surface of a normal water conservancy project building is usually uniform, the corresponding temperature distribution chaos of each monitoring area with normal anti-seepage quality is usually small and the values ​​are close. Therefore, based on this feature, a more accurate judgment of the degree of temperature abnormality can be made based on the temperature distribution chaos and the outstanding temperature distribution chaos of each monitoring area relative to other monitoring areas.

[0032] Further considering that there is a certain monitoring error in thermal imaging data, the surface humidity of the monitoring area is further analyzed to measure the credibility of the temperature anomaly. After the water stamping on the surface of the water conservancy project building anti-seepage layer is completed, when the anti-seepage layer in the monitoring area leaks, its surface anti-seepage layer coating will absorb moisture, thereby bubbles appear, and due to the leakage of moisture, the corresponding monitoring area will usually also show a humid characteristic, and the humidity deviation is greater than that of other normal monitoring areas. Therefore, this application determines the possibility of leakage in each monitoring area based on the humidity monitoring data of the monitoring area, the number of surface bubbles, and the deviation of the humidity monitoring data relative to other monitoring areas; thereby, a more accurate anti-seepage quality assessment coefficient is measured based on the degree of temperature anomaly combined with the possibility of leakage, so that the accuracy of anti-seepage quality monitoring of water conservancy project buildings based on the anti-seepage quality assessment coefficient is higher. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0034] Figure 1 A schematic diagram of the main structure of a water conservancy project building anti-seepage quality monitoring device provided by one embodiment of the present invention;

[0035] Figure 2 A side view of the main structure of a water conservancy project construction anti-seepage quality monitoring device provided by one embodiment of the present invention;

[0036] Figure 3A schematic diagram of a mobile support structure of a water conservancy project building anti-seepage quality monitoring device provided by an embodiment of the present invention;

[0037] Figure 4 A schematic flow chart of a data processing process of a water conservancy project construction anti-seepage quality monitoring device provided by an embodiment of the present invention;

[0038] In the figure, 1-water conservancy engineering building; 2-sliding track; 3-monitoring body fixing device; 4-monitoring data integration center; 5-conductor connecting line; 6-movable bracket; 7-pulley; 8-movable bracket pulley; 9-infrared thermal imager; 10-fan; 11-ultrasonic hygrometer; 12-image collector; 13-spray marking equipment. DETAILED DESCRIPTION

[0039] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of the anti-seepage quality monitoring equipment for water conservancy engineering buildings proposed in accordance with the present invention, its specific implementation method, structure, characteristics and effects, in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment, and the specific features, structures or characteristics in one or more embodiments may be combined in any suitable form. In addition, the terms "first" and "second" are used only for descriptive purposes and cannot be understood as implying or suggesting relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features.

[0040] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0041] The specific scheme of the water conservancy project construction anti-seepage quality monitoring equipment provided by the present invention is described in detail below with reference to the accompanying drawings.

[0042] This application provides a water conservancy project construction anti-seepage quality monitoring equipment, please refer to Figure 1, which shows a schematic diagram of the main structure of a water conservancy engineering building anti-seepage quality monitoring device provided by an embodiment of the present invention, the main structure includes: a water conservancy engineering building 1, a sliding track 2, a monitoring body fixing device 3, a monitoring data integration center 4, a wire connecting line 5, a mobile bracket 6, a pulley 7, a mobile bracket pulley 8, an infrared thermal imager 9, a fan 10, an ultrasonic hygrometer 11, an image collector 12 and a spray marking device 13. The sliding track 2 is installed above the water conservancy engineering building 1, the monitoring data integration center 4 is fixed on the monitoring body fixing device 3, and the monitoring body fixing device 3 is installed on the sliding track 2 and slides along the sliding track 2; one end of the wire connecting line 5 is connected to the monitoring body fixing device 3, and the other end is connected to the mobile bracket 6, and the mobile bracket 6 is suspended on the surface of the water conservancy engineering building 1 through the pulley 7; and the wire connecting line can freely adjust the length, and combined with the sliding track 2, the mobile bracket 6 can be suspended at a certain height on the surface of the water conservancy engineering building 1, and the mobile bracket 6 is parallel to the surface of the water conservancy engineering building 1. Please refer to Figure 2 , which shows a side view of the main structure of a water conservancy engineering construction anti-seepage quality monitoring device provided by an embodiment of the present invention, which includes a water conservancy engineering building 1, a pulley 7, a conductor connecting line 5 and a movable bracket 6, and the structural position distribution is more clearly characterized from the side.

[0043] The fan 10, the mobile support pulley 8, the spray marking device 13, the ultrasonic hygrometer 11, the infrared thermal imager 9 and the image collector 12 are all installed on the mobile support 6; see Figure 3, which shows a schematic diagram of the structure of a mobile support of a water conservancy engineering building anti-seepage quality monitoring device provided by an embodiment of the present invention, including: a mobile support 6, a fan 10, a mobile support pulley 8, a spray marking device 13, an ultrasonic hygrometer 11, an infrared thermal imager 9 and an image collector 12. The ultrasonic hygrometer 11 is used to collect humidity monitoring data; the infrared thermal imager 9 is used to collect temperature monitoring values; the image collector 12 is used to collect surface images of the monitoring area; the pulley of the mobile support pulley 8 contacts the surface of the water conservancy engineering building 1, and is used to adjust the hovering position of the mobile support 6; the spray marking device 13 is used to mark the area with unqualified anti-seepage quality; the fan 10 is used to reduce the degree of interference of the infrared thermal imager 9 with the ambient temperature, so that the temperature monitoring environment is maintained in a relatively stable state, reducing the impact on the thermal imaging data, so that the monitored temperature monitoring value is more accurate; the mobile support pulley 8, the spray marking device 13, the ultrasonic hygrometer 11, the infrared thermal imager 9 and the image collector 1 2 are connected to the monitoring data integration center 4 by signals; the monitoring data integration center 4 controls the mobile bracket pulley 8 to move on the surface of the water conservancy engineering building 1, so that the mobile bracket 6 moves to different positions, and the image collector 12 collects all the surface images of the monitoring area while the mobile bracket 6 moves, so that all the surface images of the monitoring area can cover the entire surface of the water conservancy engineering building 1, and the surface images of the monitoring areas do not overlap; that is, the embodiment of the present invention uses the area corresponding to each surface image of the monitoring area captured by the image collector 12 as the corresponding monitoring area; in a specific implementation method of the embodiment of the present invention, the image collector uses a CCD camera, and the shooting equipment can be adjusted automatically.

[0044] The monitoring data integration center 4 can be a data processing chip such as a CPU, MCU, or a data processing device such as a computer host. In addition, the output ends corresponding to the ultrasonic hygrometer 11, the infrared thermal imager 9, and the image collector 12 are connected to the input end of the monitoring data integration center 4, and the output end of the monitoring data integration center 4 is connected to the input end of the mobile support pulley 8 and the spray marking device 13, that is, the mobile support pulley 8 and the spray marking device 13 are controlled by the monitoring data integration center 4, and a wired connection can be realized through a data transmission line, and a wireless connection can also be realized through wireless communication methods such as Bluetooth and WiFi.

[0045] After collecting humidity monitoring data through the ultrasonic hygrometer 11, collecting temperature monitoring values ​​through the infrared thermal imager 9, and collecting the surface image of the monitoring area through the image collector 12, the collected data signals are transmitted to the monitoring data integration center 4. The monitoring data integration center performs water conservancy project construction anti-seepage quality monitoring according to the humidity monitoring data collected by the ultrasonic hygrometer, the temperature monitoring values ​​collected by the infrared thermal imager, and the surface image of the monitoring area collected by the image collector according to the predetermined data processing process. Please refer to Figure 4 , which shows a flow chart of a data processing process of a water conservancy project building anti-seepage quality monitoring device provided by an embodiment of the present invention, comprising the following steps:

[0046] Step S401: Obtain humidity monitoring data, the number of surface bubbles, and the temperature monitoring value at each monitoring point in each monitoring area on the surface of a water conservancy project building.

[0047] In a specific implementation of the embodiment of the present invention, the position measured by each infrared imager in each monitoring area is used as the corresponding position of each monitoring point, and the corresponding temperature monitoring value is the temperature value measured by the corresponding infrared imager.

[0048] In a specific implementation of an embodiment of the present invention, the surface image of the monitoring area of ​​each monitoring area is input into a trained deep learning model, and the number of surface bubbles in the corresponding monitoring area is output; the deep learning model uses a convolutional neural network, and the implementer can adjust it according to the specific implementation environment.

[0049] Step S402: Determine the degree of temperature anomaly in each monitoring area based on the fluctuation of the temperature monitoring values ​​at each monitoring point in each monitoring area; determine the degree of temperature anomaly in each monitoring area based on the temperature distribution anomaly and the prominence of the temperature distribution anomaly in each monitoring area relative to other monitoring areas.

[0050] For each monitoring area on the surface of a water conservancy project building, its surface will be covered with an anti-seepage layer, and the surface of the anti-seepage layer shows a uniform temperature distribution; therefore, when the anti-seepage layer on the surface of the monitoring area is unevenly coated or there is water penetration, the corresponding temperature distribution will be uneven, that is, chaotic; therefore, this application first determines the temperature distribution chaos of each monitoring area according to the fluctuation of the temperature monitoring value at each monitoring point in each monitoring area. In addition, since the anti-seepage layer on the surface of a normal water conservancy project building is usually uniform, the corresponding temperature distribution chaos of each monitoring area with normal anti-seepage quality is usually small and the values ​​are close, so according to this feature, on the basis of the temperature distribution chaos, combined with the outstanding temperature distribution chaos of each monitoring area relative to other monitoring areas, a more accurate judgment of the degree of temperature anomaly can be made; for each monitoring area, the greater the corresponding temperature distribution chaos, and the more prominent its temperature distribution chaos is relative to other areas, the more abnormal the temperature distribution of the monitoring area is, the more likely it is that there will be quality problems in the surface anti-seepage layer, and the worse the corresponding anti-seepage quality is.

[0051] Preferably, in some possible implementations of the embodiments of the present invention, the process of obtaining the temperature distribution disorder degree includes:

[0052] Calculate the variance of the temperature monitoring values ​​and the range of the temperature monitoring values ​​at all monitoring points in each monitoring area; determine the degree of temperature distribution chaos in each monitoring area based on the variance of the temperature monitoring values ​​and the range of the temperature monitoring values. For each monitoring area, the more uneven the corresponding temperature distribution is, that is, the stronger the volatility is, the more chaotic the corresponding temperature distribution is, and the range reflects the fluctuation range of a set of data, and the variance reflects the degree of discreteness of a set of data, which can reflect the fluctuation characteristics of a set of data to a certain extent; therefore, the larger the variance of the temperature monitoring values ​​and the larger the range of the temperature monitoring values, the more chaotic the temperature distribution of the corresponding monitoring area is, that is, the stronger the volatility is, and the greater the degree of chaos of the corresponding temperature distribution is; therefore, the variance of the temperature monitoring values ​​and the range of the temperature monitoring values ​​are both positively correlated with the degree of chaos of the temperature distribution.

[0053] Preferably, in some possible implementations of the embodiments of the present invention, determining the temperature distribution disorder of each monitoring area according to the temperature monitoring value variance and the temperature monitoring value range includes:

[0054] The temperature distribution disorder of each monitoring area is determined according to the product of the temperature monitoring value variance and the temperature monitoring value range. It should be noted that, in addition to the product, the implementer can also calculate the temperature distribution disorder by other methods according to the correlation, such as the normalized value of the mean and the sum, which will not be further elaborated here.

[0055] In a specific implementation of the embodiment of the present invention, the method for obtaining the temperature distribution disorder is expressed in the formula as follows: ; For the The degree of temperature distribution disorder in each monitoring area; For the The variance of the temperature monitoring values ​​at all monitoring points in the monitoring area; For the The maximum value of the temperature monitoring value at all monitoring points in the monitoring area; For the The minimum value of the temperature monitoring value at all monitoring points in the monitoring area; For the The temperature monitoring values ​​at all monitoring points in the monitoring area are extremely poor; is the absolute value symbol.

[0056] Preferably, in some possible implementations of the embodiments of the present invention, the process of obtaining the degree of temperature anomaly includes:

[0057] Each monitoring area is taken as the target area in turn, and other monitoring areas outside the target area are taken as the corresponding reference areas; according to the difference between the temperature distribution disorder of the target area and the temperature distribution disorder of each corresponding reference area, the reference temperature distribution deviation of each reference area is determined; according to the temperature distribution disorder of the target area and the overall size of the reference temperature distribution deviation of each corresponding reference area, the temperature anomaly degree of the target area is determined. The larger the corresponding reference temperature distribution deviation, the larger the deviation of the temperature distribution disorder between the target area and the corresponding reference area. Therefore, if the overall deviation of the reference temperature distribution between the target area and all corresponding reference areas is larger, it means that the temperature distribution disorder of the target area is relatively more prominent, and the temperature is more abnormal; and the temperature distribution disorder can also characterize the abnormal temperature to a certain extent. Therefore, the temperature anomaly degree of the target area is determined in combination with the temperature distribution disorder of the target area and the overall size of the reference temperature distribution deviation of each corresponding reference area. The larger the corresponding temperature anomaly degree, the more abnormal the temperature distribution of the monitoring area is, the more likely the surface anti-seepage layer will have quality problems, and the corresponding anti-seepage quality will be worse. It should be noted that other monitoring areas outside the target area are all monitoring areas except the target area.

[0058] In some possible implementations of the embodiments of the present invention, determining the temperature anomaly degree of the target area according to the overall size of the reference temperature distribution deviations of the reference areas corresponding to the target area includes:

[0059] The product of the mean of the reference temperature distribution deviations of all reference areas corresponding to the target area and the temperature distribution disorder of the target area is used as the temperature anomaly degree of the target area. It should be noted that in addition to the product, the implementer can also calculate the temperature anomaly degree by other methods according to the correlation, such as the normalized value of the mean and the sum, which will not be further elaborated here.

[0060] In a specific implementation of the embodiment of the present invention, the process of obtaining the temperature anomaly degree is expressed by the formula: ;in, For the The degree of temperature anomaly in each monitoring area; For the The degree of temperature distribution disorder in each monitoring area; For the The number of reference areas in the monitoring area, that is, The number of other monitoring areas outside the monitoring area; For the The monitoring area corresponds to The degree of disorder of temperature distribution in a reference area; For the The monitoring area corresponds to The reference temperature distribution deviation of the reference area.

[0061] Step S403: Determine the leakage possibility of each monitoring area according to the humidity monitoring data, the number of surface bubbles, and the deviation of the humidity monitoring data of each monitoring area relative to the humidity monitoring data of other monitoring areas.

[0062] Further considering that there is a certain monitoring error in the thermal imaging data, the surface humidity of the monitoring area is further analyzed to measure the credibility of the temperature anomaly. After the water stamping on the surface of the anti-seepage layer of the water conservancy project building is completed, when the anti-seepage layer of the monitoring area leaks, the surface anti-seepage layer coating will absorb moisture, thereby bubbles appear, and due to the leakage of moisture, the corresponding monitoring area will usually also show a humid characteristic, and the humidity deviation is greater than that of other normal monitoring areas. Therefore, this application determines the possibility of leakage in each monitoring area based on the humidity monitoring data of the monitoring area, the number of surface bubbles, and the deviation of the humidity monitoring data relative to other monitoring areas. The greater the corresponding leakage possibility, the more likely it is that the monitoring area is to have infiltration, and the worse the corresponding anti-seepage quality is.

[0063] Preferably, in some possible implementations of the embodiments of the present invention, the process of obtaining the leakage possibility includes:

[0064] Calculate the difference in humidity monitoring data between each monitoring area and each other monitoring area; take the mean of all humidity monitoring data differences corresponding to each monitoring area as the reference humidity distribution deviation of each monitoring area; determine the possibility of leakage in each monitoring area based on the humidity monitoring data, reference humidity distribution deviation and number of surface bubbles in each monitoring area. For the monitoring area where leakage occurs, first of all, the larger the humidity monitoring data, the more likely it is that the monitoring area will leak; and on this basis, the larger the calculated reference humidity distribution deviation, the larger the humidity deviation of the corresponding monitoring area compared to other monitoring areas, and the greater the possibility of leakage. The bubbles on the surface of the monitoring area are caused by leakage. The more bubbles there are, the greater the impact of leakage, and the greater the corresponding possibility of leakage; therefore, the humidity monitoring data, reference humidity distribution deviation and number of surface bubbles are all positively correlated with the possibility of leakage.

[0065] Preferably, in some possible implementations of the embodiments of the present invention, determining the leakage possibility of each monitoring area according to the humidity monitoring data of each monitoring area, the reference humidity distribution deviation and the number of surface bubbles includes:

[0066] The product of the humidity monitoring data, the reference humidity distribution deviation and the number of surface bubbles in each monitoring area is normalized to determine the leakage possibility of each monitoring area. It should be noted that in addition to the normalized value of the product, the implementer can also calculate the leakage possibility by other methods according to the correlation, such as the normalized value of the mean, the normalized value of the sum, etc., which will not be further elaborated here.

[0067] In a specific implementation of the embodiment of the present invention, the calculation process of the leakage possibility is expressed by the formula: ; For the Leakage potential in each monitoring area; For the The number of surface bubbles in each monitoring area; For the Humidity monitoring data of each monitoring area; For the The monitoring area outside Humidity monitoring data of each monitoring area; For the The monitoring area and the Differences in humidity monitoring data between monitoring areas; For the The reference humidity distribution deviation of each monitoring area; is the absolute value symbol. It is a linear normalization function. The implementer can adjust the normalization method according to the specific implementation environment.

[0068] Step S404: Determine the anti-seepage quality assessment coefficient of each monitoring area according to the degree of temperature anomaly and the possibility of leakage; and monitor the anti-seepage quality of water conservancy project buildings according to the anti-seepage quality assessment coefficient.

[0069] For each monitoring area, the greater the corresponding temperature anomaly and the greater the possibility of leakage, the greater the impact of leakage on the area and the worse the corresponding anti-seepage quality; therefore, the anti-seepage quality assessment is carried out in combination with the temperature anomaly and the possibility of leakage.

[0070] Preferably, in some possible implementations of the embodiments of the present invention, the process of obtaining the anti-seepage quality assessment coefficient includes:

[0071] The product of the temperature anomaly degree and the leakage possibility is negatively correlated and normalized to determine the anti-seepage quality assessment coefficient of each monitoring area. Since the temperature anomaly degree and the leakage possibility are negatively correlated with the anti-seepage quality, the temperature anomaly degree and the leakage possibility are combined by multiplication and negatively correlated normalized to determine the anti-seepage quality assessment coefficient, and the purpose of normalization is to limit the value range of the anti-seepage quality assessment index to 0 to 1, making the assessment of anti-seepage quality more intuitive.

[0072] In a specific implementation of the embodiment of the present invention, the process of obtaining the anti-seepage quality evaluation coefficient is expressed by the formula: ;in, For the The anti-seepage quality assessment coefficient of each monitoring area; For the The degree of temperature anomaly in each monitoring area; For the Leakage potential in each monitoring area; It is a linear normalization function. The implementer can adjust the normalization method according to the specific implementation environment.

[0073] Preferably, in some possible implementations of the embodiments of the present invention, monitoring the anti-seepage quality of water conservancy engineering buildings according to the anti-seepage quality assessment coefficient includes:

[0074] The monitoring area whose anti-seepage quality assessment coefficient is less than the preset assessment threshold is judged as an area with unqualified anti-seepage quality of water conservancy project construction, and is marked by a spray marking device. In a specific implementation method of an embodiment of the present invention, the preset assessment threshold is set to 0.57, which can be adjusted according to the specific implementation environment. The larger the anti-seepage quality assessment coefficient, the better the anti-seepage quality; conversely, the smaller the anti-seepage quality assessment coefficient, the worse the anti-seepage quality; therefore, the quality area is evaluated by setting a threshold. The monitoring area marked by the spray marking device is also an area with unqualified anti-seepage quality, and it is necessary to maintain the area in time to prevent safety hazards.

[0075] To summarize, a water conservancy project construction anti-seepage quality monitoring device first determines the degree of temperature anomaly in each monitoring area based on the fluctuation of the temperature monitoring value in each monitoring area monitored by the infrared thermal imager; further, the degree of temperature anomaly in each monitoring area is characterized by credibility according to the humidity monitoring data in each monitoring area and the leakage possibility determined by the bubble distribution, so as to measure the anti-seepage quality assessment coefficient more accurately in combination with the degree of temperature anomaly and the leakage possibility, and solves the problem that the infrared thermal imaging method may have a delayed response to temperature changes, resulting in certain monitoring errors in the thermal imaging data monitored in real time, affecting the accuracy of the anti-seepage quality assessment of water conservancy project buildings, so that more accurate anti-seepage quality monitoring of water conservancy project buildings can be carried out according to the anti-seepage quality assessment coefficient.

[0076] It should be noted that the sequence of the above embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0077] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

Claims

1. A water conservancy project construction anti-seepage quality monitoring device, characterized in that: It includes a monitoring body fixing device, a sliding track, a monitoring data integration center, a pulley, a wire connecting line, a mobile bracket, an ultrasonic hygrometer, an infrared thermal imager and an image collector; the sliding track is installed above the water conservancy project building, the monitoring data integration center is fixed on the monitoring body fixing device, the monitoring body fixing device is installed on the sliding track and slides along the sliding track; one end of the wire connecting line is connected to the monitoring body fixing device, and the other end is connected to the mobile bracket, and the mobile bracket is suspended on the surface of the water conservancy project building through the pulley; the ultrasonic hygrometer, the infrared thermal imager and the image collector are all installed on the mobile bracket. The ultrasonic hygrometer is used to collect humidity monitoring data; the infrared thermal imager is used to collect temperature monitoring values; the image collector is used to collect surface images of the monitoring area; the ultrasonic hygrometer, the infrared thermal imager and the image collector are all connected to the monitoring data integration center by signal; the monitoring data integration center obtains the humidity monitoring data, the number of surface bubbles and the temperature monitoring value at each monitoring point in each monitoring area of ​​the water conservancy project building surface according to the humidity monitoring data collected by the ultrasonic hygrometer, the temperature monitoring value collected by the infrared thermal imager and the surface image of the monitoring area collected by the image collector; Determine the temperature distribution disorder of each monitoring area according to the fluctuation of the temperature monitoring values ​​at each monitoring point in each monitoring area; determine the temperature anomaly degree of each monitoring area according to the temperature distribution disorder and the prominence of the temperature distribution disorder of each monitoring area relative to other monitoring areas; Determine the possibility of leakage in each monitoring area according to the humidity monitoring data, the number of bubbles on the surface, and the deviation of the humidity monitoring data of each monitoring area relative to the humidity monitoring data of other monitoring areas; Determine the anti-seepage quality assessment coefficient of each monitoring area according to the temperature anomaly degree and the leakage possibility; Conducting water conservancy project construction anti-seepage quality monitoring according to the anti-seepage quality assessment coefficient; The process of obtaining the temperature distribution disorder degree includes: Calculate the variance and range of the temperature monitoring values ​​at all monitoring points in each monitoring area; Determine the temperature distribution disorder of each monitoring area according to the temperature monitoring value variance and the temperature monitoring value range; the temperature monitoring value variance and the temperature monitoring value range are both positively correlated with the temperature distribution disorder; Determining the temperature distribution disorder of each monitoring area according to the temperature monitoring value variance and the temperature monitoring value range includes: Determine the temperature distribution disorder of each monitoring area according to the product of the temperature monitoring value variance and the temperature monitoring value range; The process of obtaining the temperature anomaly degree includes: Taking each monitoring area as a target area in turn, and taking other monitoring areas outside the target area as corresponding reference areas; Determining the reference temperature distribution deviation of each reference area according to the difference between the temperature distribution disorder of the target area and the temperature distribution disorder of each corresponding reference area; Determine the temperature anomaly degree of the target area according to the temperature distribution disorder of the target area and the overall size of the reference temperature distribution deviation of each corresponding reference area; Determining the temperature anomaly degree of the target area according to the overall size of the reference temperature distribution deviations of the reference areas corresponding to the target area includes: The product of the mean value of the reference temperature distribution deviations of all reference areas corresponding to the target area and the temperature distribution disorder of the target area is taken as the temperature anomaly degree of the target area; The process of obtaining the leakage possibility includes: Calculate the difference in humidity monitoring data between each monitoring area and each other monitoring area; take the mean of all humidity monitoring data differences corresponding to each monitoring area as the reference humidity distribution deviation of each monitoring area; Determine the leakage possibility of each monitoring area according to the humidity monitoring data, reference humidity distribution deviation and surface bubble number of each monitoring area; the humidity monitoring data, reference humidity distribution deviation and surface bubble number are all positively correlated with the leakage possibility; Determining the leakage possibility of each monitoring area according to the humidity monitoring data of each monitoring area, the reference humidity distribution deviation and the number of surface bubbles includes: The product of the humidity monitoring data, the reference humidity distribution deviation and the number of surface bubbles in each monitoring area was normalized to determine the leakage possibility of each monitoring area.

2. The water conservancy engineering construction anti-seepage quality monitoring equipment according to claim 1 is characterized in that: The process of obtaining the anti-seepage quality assessment coefficient includes: The product of the temperature anomaly degree and the leakage possibility is normalized by negative correlation to determine the anti-seepage quality assessment coefficient of each monitoring area.

3. The water conservancy engineering construction anti-seepage quality monitoring equipment according to claim 2 is characterized in that: The anti-seepage quality monitoring of water conservancy engineering buildings according to the anti-seepage quality assessment coefficient includes: The monitoring area whose anti-seepage quality assessment coefficient is less than the preset assessment threshold is judged as an area with unqualified anti-seepage quality of water conservancy project construction, and is marked by a jet marking device.

4. The water conservancy engineering construction anti-seepage quality monitoring equipment according to claim 3 is characterized in that: The preset evaluation threshold is set to 0.57.

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