A dam detection method and system based on drone

Abstract

The present application relates to a dam inspection method and system based on drones, and relates to the field of safety inspection technology. The method includes obtaining a regional inspection time point; determining the inspection interval duration based on the regional inspection time point and the current time point; constructing a historical interval to obtain the crack interval duration; determining the effective interval duration based on all crack interval durations in a single local area, and defining a local area where the inspection interval duration is greater than the effective interval duration as a required inspection area; determining regional inspection points in the required inspection area, and constructing a simulated inspection path based on each regional inspection point and a starting point, and determining the required flight distance based on the simulated inspection path; determining the required flight distance with the minimum value and defining the corresponding simulated inspection path as a used inspection path, and controlling the drone to move along the used inspection path at the starting point to obtain dam inspection images. The present application has the effect of improving the inspection efficiency of dam inspections.

Description

Technical Field

[0001] The present application relates to the field of safety detection technology, and in particular to a dam detection method and system based on drones. Background Art

[0002] A dam is a structure used to prevent water from entering or leaving the dam, protecting the lives and property of the surrounding area. By constructing sluices, channels, and other facilities on the dam, water flow can be regulated for agricultural irrigation and the rational use of water resources. Dam leakage refers to the infiltration or leakage of water or moisture from the dam or levee structure through cracks, holes, or other permeable channels. Dam leakage can adversely affect the stability of the dam, making the detection of dam cracks a crucial step. Once the dam is inspected, cracks can be repaired promptly if no leakage is detected, preventing losses.

[0003] At present, the inspection of dams is often carried out using drones equipped with image capture equipment. That is, the area to be inspected is generated based on the dam's own parameters, and the staff determines the flight path of the drone in the inspection area so that the drone can obtain images of various parts of the dam during flight inspection, and thus cracks in the dam can be determined based on the images.

[0004] In the above-mentioned related technologies, precise detection of each location is required when performing crack detection. However, during the actual use of the dam, due to the influence of water erosion, the probability of cracks occurring at each location point is different. Therefore, when using the above-mentioned scheme for detection, there will be many invalid detections, resulting in low detection efficiency, which is not convenient for daily general inspections and there is still room for improvement. Summary of the Invention

[0005] In order to improve the detection efficiency of dam inspection, the present application provides a dam inspection method and system based on drones.

[0006] In the first aspect, the present application provides a dam inspection method based on drones, which adopts the following technical solutions:

[0007] A dam inspection method based on drone, comprising:

[0008] Obtaining regional detection time points of each preset local area on the dam;

[0009] Determine the detection interval length based on the regional detection time point and the current time point;

[0010] Construct a historical interval on a preset time axis with the current time point as the end point and a width of a preset historical length, and obtain the crack interval duration of each local area in the historical interval;

[0011] In a single local area, the effective interval duration is calculated based on all crack interval durations, and the local area where the detection interval duration is longer than the effective interval duration is defined as the area requiring detection;

[0012] Determine regional detection points in the required detection area, randomly sort the regional detection points, and connect them in series with a preset starting point to construct a simulated detection path, and determine the required flight distance based on the simulated detection path;

[0013] The required flight distance with the minimum value is determined according to the preset sorting rules, and the simulated detection path corresponding to the required flight distance is defined as the use detection path. The drone is controlled to move along the use detection path at the starting point to obtain the dam detection image.

[0014] Optionally, the step of calculating the effective interval duration based on all crack interval durations in a single local area includes:

[0015] Obtain the crack determination time point corresponding to the crack interval duration;

[0016] Determine the data interval length based on the crack determination time point and the current time point, and define the data interval length with the smallest value as the benchmark interval length;

[0017] Calculate the extension ratio based on the data interval and the benchmark interval;

[0018] Determine the relative reliability coefficient corresponding to the extension ratio according to the preset reliable matching relationship, and calculate the reliable calculation weight corresponding to each crack interval length according to each relative reliability coefficient;

[0019] The simulation interval is determined by calculating the interval length of each crack and the corresponding reliable calculation weight;

[0020] Determine whether the simulation interval is greater than the preset fixed interval;

[0021] If the simulation interval duration is not greater than the fixed interval duration, the simulation interval duration is determined as the effective interval duration;

[0022] If the simulation interval duration is greater than the fixed interval duration, the fixed interval duration is determined as the effective interval duration.

[0023] Optionally, after the required flight distance is determined, the drone-based dam inspection method may further include:

[0024] The local area that is not the required detection area is defined as the waiting area;

[0025] Determine the detection coverage area based on the current simulated detection path and the preset unit coverage area;

[0026] The area within the detection coverage area of ​​a single waiting area is defined as an incidental area, and the incidental ratio is determined based on the incidental area and the waiting area. The waiting area whose incidental ratio is greater than the preset effective detection ratio is defined as an effective area;

[0027] The duration interval ratio is determined by calculating the duration of the detection interval in the effective area and the duration of the effective interval;

[0028] Determine the simulated distance reduction corresponding to the time interval ratio based on the preset candidate matching relationship, and sum up all the simulated distance reductions to determine the overall distance reduction;

[0029] The required flight distance is updated by performing a difference calculation based on the overall reduction distance and the required flight distance.

[0030] Optionally, after the required flight route is updated, the drone-based dam inspection method may further include:

[0031] Determine whether there are at least two simulated detection paths with the same required flight distance and the minimum required flight distance;

[0032] If there are not at least two simulated detection paths with the same required flight distance and the minimum required flight distance, the simulated detection path corresponding to the minimum required flight distance is defined as the used detection path;

[0033] If there are at least two simulated detection paths with the same required flight distance and the smallest required flight distance, the simulated detection path corresponding to the smallest required flight distance is defined as the alternative detection path;

[0034] In the alternative detection path, the effective area where the ratio of the time interval is greater than the preset ratio of the boundary interval is defined as a high-value area;

[0035] The high-value areas are counted to determine the high-value quantity, and the high-value quantity with the largest value is determined according to the sorting rule, and the alternative detection path corresponding to the high-value quantity is defined as the detection path to be used.

[0036] Optionally, after the dam inspection image is acquired, the dam inspection method based on a drone further includes:

[0037] Perform feature recognition based on the dam inspection image to determine the dam crack characteristics;

[0038] Determine whether the dam crack feature has an intersection with the contour line of the local area corresponding to the dam detection image;

[0039] If the crack feature of the dam does not intersect with the contour line of the local area corresponding to the dam detection image, a detection completion signal is output;

[0040] If there is an intersection between the dam crack feature and the contour line of the local area corresponding to the dam detection image, the local area with the intersection on the remaining contour lines is defined as the area to be tested;

[0041] The area to be tested that is not the required detection area and the effective area is defined as a secondary area, and a secondary operation path is constructed based on the secondary area, and the UAV is controlled to move along the secondary operation path to obtain the embankment detection image again.

[0042] Optionally, after the secondary area is determined, the drone-based dam inspection method also includes:

[0043] The effective area where embankment crack characteristics exist is defined as the crack area;

[0044] The proportion of time intervals corresponding to the crack area is defined as the crack existence proportion;

[0045] Randomly select a crack existence ratio as the center existence ratio, and construct a similar ratio range based on the center existence ratio and the preset similar ratio;

[0046] Count the proportions of cracks within a similar range to determine the number of cracks present inside, and count all the cracks to determine the overall number of cracks present.

[0047] Calculate the internal quantity and the overall quantity to determine the internal quantity ratio;

[0048] Determine whether the internal quantity ratio is greater than the preset aggregate quantity ratio;

[0049] If there is no situation where the proportion of internal quantity is greater than the proportion of aggregate quantity, the currently determined secondary area is maintained;

[0050] If the proportion of internal quantity is greater than the proportion of aggregate quantity, the proportion of cracks in the range close to the maximum internal quantity proportion will be averaged to determine the advance average proportion.

[0051] The local area whose average advance ratio is greater than the corresponding time interval ratio and is not a demand detection area or a valid area is determined as a secondary area.

[0052] Optionally, after the detection completion signal is output, the dam detection method based on the drone further includes:

[0053] Get the number of detected areas and the number of abnormal areas;

[0054] Calculate the abnormal detection ratio based on the number of detection areas and the number of abnormal areas;

[0055] The detection evaluation coefficient corresponding to the abnormal detection ratio is determined based on the preset evaluation matching relationship.

[0056] In a second aspect, the present application provides a dam inspection system based on drones, which adopts the following technical solutions:

[0057] A dam inspection system based on drones, comprising:

[0058] An acquisition module is used to obtain regional detection time points of each preset local area on the dam;

[0059] A processing module, connected to the acquisition module, for storing and processing information;

[0060] The processing module determines the detection interval duration based on the regional detection time point and the current time point;

[0061] The processing module constructs a historical interval with the current time point as the end point and a width of the preset historical length on the preset time axis, and obtains the crack interval length of each local area in the historical interval;

[0062] The processing module calculates the effective interval duration based on all crack interval durations in a single local area, and defines the local area where the detection interval duration is longer than the effective interval duration as the required detection area;

[0063] The processing module determines regional detection points on the required detection area, randomly sorts the regional detection points, and connects them in series with a preset starting point to construct a simulated detection path, and determines the required flight distance based on the simulated detection path;

[0064] The processing module determines the required flight distance with the minimum value according to a preset sorting rule, defines the simulated detection path corresponding to the required flight distance as the used detection path, and controls the drone to move along the used detection path at the starting point to obtain the dam detection image.

[0065] In summary, this application includes at least one of the following beneficial technical effects:

[0066] When using drones to conduct routine inspections of cracks in dams, the frequency of cracks that have occurred in each dam in history can be used to detect areas with a high probability of cracks at the current time point, thereby reducing areas of invalid inspections and improving the inspection efficiency of dams.

[0067] In the process of selecting the drone path, the inspection conditions of the areas to be passed by are fully considered to set a suitable path for the drone to fly, so as to achieve the best overall inspection effect;

[0068] The second flight path is determined based on the crack conditions determined by the first flight, thereby minimizing invalid drone detection and improving overall detection efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] Figure 1 It is a flow chart of the UAV-based dam inspection method.

[0070] Figure 2 It is a module flow chart of the UAV-based dam inspection method. DETAILED DESCRIPTION

[0071] In order to make the purpose, technical solutions and advantages of this application more clear, the following Figure 1-Figure 2 It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application.

[0072] The embodiments of the present application are described in further detail below with reference to the accompanying drawings.

[0073] The present application embodiment discloses a dam detection method based on drone, referring to Figure 1 ,The method process of the UAV-based embankment inspection method includes the ,following steps:

[0074] Step S100: obtaining regional detection time points of each preset local area on the dam.

[0075] The local area is the area designated by the staff for crack detection based on the dam. A local area means that when the drone hovers directly above the center point of the area, it can completely capture the image of the area. The specific division of the local area is determined in advance by the staff and will not be elaborated here. The regional detection time point is the time point when the local area was last detected by the drone using a drone.

[0076] Step S101: Determine the detection interval duration according to the area detection time point and the current time point.

[0077] The detection interval is the time interval between the last detection of the local area, that is, the time interval between the regional detection time point and the current time point.

[0078] Step S102: constructing a historical interval with the current time point as the end point and a width of a preset historical duration on a preset time axis, and obtaining the crack interval duration of each local area in the historical interval.

[0079] The time axis is a coordinate axis formed by the combination of various time points. The coordinate axis points from the time points that have passed to the time points that have not yet arrived, where the time points that have passed are on the left side of the time axis, and the left side is defined as the front end of the time axis; the historical duration is the duration set by the staff to obtain data on the historical crack conditions of the dam, and the historical interval is constructed to facilitate the acquisition of data within the historical duration; the crack interval duration is the time interval between two adjacent crack occurrences detected in the local area in the historical interval.

[0080] Step S103: Calculate the effective interval duration based on all crack interval durations in a single local area, and define the local area where the detection interval duration is longer than the effective interval duration as a detection-required area.

[0081] The effective interval duration is the interval duration for determining the common occurrence of cracks in the local area. It can be obtained by calculating the average value of all crack interval durations, or by the method of steps S200-S2052. When the detection interval duration is greater than the effective interval duration, it indicates that there is a high possibility of cracks occurring in the area. Therefore, it is defined as a detection-required area to distinguish different local areas for subsequent analysis.

[0082] Step S104: determining regional detection points on the required detection area, and randomly sorting the regional detection points and connecting them in series with a preset starting point to construct a simulated detection path, and determining the required flight distance based on the simulated detection path.

[0083] The regional detection point is the location point where the drone can obtain the overall image of the required detection area after hovering. Generally, the regional detection point is the center point of the required detection area; the starting point is the location point before the drone starts working, which can be obtained by installing a positioning device on the drone. The simulated detection path is the path obtained by connecting all the sorted regional detection points in series with the starting point as the first endpoint, that is, the drone can obtain images of each required detection area by moving according to the simulated detection path; the required flight distance is the path that the drone needs to move when performing flight operations according to the simulated detection path.

[0084] Step S105: Determine the required flight distance with the minimum value according to the preset sorting rules, and define the simulated detection path corresponding to the required flight distance as the used detection path, and control the UAV to move along the used detection path at the starting point to obtain the dam detection image.

[0085] The sorting rule is a method set by the staff to sort the size of the values, such as the bubble method. The sorting rule can be used to determine the required flight distance with the minimum value. That is, when the drone moves according to the simulated detection path corresponding to the required flight distance, the overall detection efficiency is the highest. At this time, it can be defined as using the detection path to control the drone operation; the dam detection image is the image of the dam surface collected by the drone during the movement.

[0086] The steps for calculating the effective interval duration based on all crack interval durations in a single local area include:

[0087] Step S200: Obtain the crack determination time point corresponding to the crack interval duration.

[0088] The crack determination time point is the time point at which the crack is discovered at the back end when determining the crack interval duration.

[0089] Step S201: determining the data interval time according to the crack determination time point and the current time point, and defining the data interval time with the smallest value as the benchmark interval time.

[0090] The data interval length is the time interval between the crack determination time point and the current time point. The benchmark interval length is defined to distinguish different data interval lengths for subsequent analysis.

[0091] Step S202: Calculate the extension ratio based on the data interval time and the benchmark interval time.

[0092] The extension ratio is the ratio of the data interval length divided by the benchmark interval length.

[0093] Step S203: determining the relative reliability coefficient corresponding to the extension ratio according to the preset reliable matching relationship, and performing calculations based on the relative reliability coefficients to determine the reliable calculation weight corresponding to the duration of each crack interval.

[0094] The relative reliability coefficient is a parameter that reflects the reliability of the data. The larger the delay ratio, the longer the interval between the corresponding data acquisition time point and the current time point, and the lower the corresponding relative reliability coefficient. The reliable matching relationship between the two is set in advance by the staff according to the actual situation; the corresponding reliability calculation weight can be obtained by summing up the relative reliability coefficients and then dividing each relative reliability coefficient by the sum.

[0095] Step S204: performing calculations based on the interval durations of the cracks and the corresponding reliable calculation weights to determine the simulation interval duration.

[0096] By multiplying the interval length of each crack by the corresponding reliable calculation weight and then summing the results, a more appropriate simulation interval length that can reflect the interval length of cracks in the local area can be obtained.

[0097] Step S205: Determine whether the simulation interval is greater than a preset fixed interval.

[0098] The fixed interval duration is the maximum duration set by the staff for a single local area to remain undetected. The purpose of the judgment is to find out whether the determined simulation interval duration is too long.

[0099] Step S2051: If the simulation interval duration is not greater than the fixed interval duration, the simulation interval duration is determined as the effective interval duration.

[0100] When the simulation interval duration is not greater than the fixed interval duration, it indicates that the simulation interval duration determined at this time is a value used for subsequent analysis, and it can be determined as the effective interval duration.

[0101] Step S2052: If the simulation interval duration is greater than the fixed interval duration, the fixed interval duration is determined as the effective interval duration.

[0102] When the simulation interval duration is greater than the fixed interval duration, it indicates that the fixed interval duration determined at this time is the value used for subsequent analysis, and it can be determined as the effective interval duration.

[0103] After the required flight distance is determined, the drone-based dam inspection method also includes:

[0104] Step S300: defining a local area that is not a detection-required area as a waiting area.

[0105] Define waiting areas to identify local areas that do not currently need to be inspected, facilitating subsequent analysis.

[0106] Step S301: determining a detection coverage area according to a current simulated detection path and a preset unit coverage area.

[0107] The unit coverage area is the area that the drone can cover and detect when it is at one point, and the detection coverage area is the area that the drone can detect after moving along the simulated detection path.

[0108] Step S302: define the area within the detection coverage area of ​​a single waiting area as an incidental area, determine the incidental proportion based on the incidental area and the waiting area, and define the waiting area whose incidental proportion is greater than the preset effective detection proportion as an effective area.

[0109] The incidental area is defined to determine the area in a single waiting area that overlaps with the detection coverage area, that is, to determine the area where the drone is detected; the incidental ratio is the ratio of the incidental area in a single waiting area, which is determined by dividing the area of ​​the incidental area by the area of ​​the waiting area; the effective detection ratio is the minimum incidental ratio set by the staff to determine that the waiting area is well detected. When the incidental ratio is greater than the effective detection ratio, it means that the drone has conducted a relatively complete detection of the waiting area during the flight. Therefore, it is defined as a valid area to distinguish different waiting areas, which is convenient for subsequent analysis.

[0110] Step S303: Calculate the duration interval ratio based on the detection interval duration of the effective area and the effective interval duration.

[0111] The duration interval ratio is the ratio of the detection interval duration determined in the effective area to the effective interval duration. The larger the value is, the more worthy the local area is to be detected.

[0112] Step S304: Determine the simulated distance reduction corresponding to the time interval ratio according to the preset candidate matching relationship, and perform sum calculation based on all the simulated distance reductions to determine the overall distance reduction.

[0113] The simulated distance reduction is a parameter value that objectively reflects whether the effective area is worthy of being detected in passing. The larger the parameter value is, the more worthy the effective area is of being detected in passing, and the corresponding time interval accounts for a larger proportion. The candidate matching relationship between the two is determined by the staff in advance through multiple tests; the overall distance reduction is the sum of all the determined simulated distance reductions.

[0114] Step S305: Calculate the difference between the overall reduced distance and the required flight distance to update the required flight distance.

[0115] The required flight distance can be updated by subtracting the overall reduction distance from the required flight distance, which facilitates the subsequent selection of a more suitable path for drone flight.

[0116] After the required flight path is updated, the drone-based dam inspection method also includes:

[0117] Step S400: Determine whether there are at least two simulated detection paths with the same required flight distance and the minimum required flight distance.

[0118] The purpose of the judgment is to find out whether there are multiple simulation detection paths that meet the requirements, so as to determine the only detection path to be used.

[0119] Step S4001: If there are not at least two minimum simulated detection paths with the same required flight distance, the simulated detection path corresponding to the minimum required flight distance is defined as the used detection path.

[0120] When there are not at least two simulated detection paths with the same required flight distance and the minimum required flight distance, it means that there is only one simulated detection path that meets the requirements. In this case, it can be determined as the detection path to be used.

[0121] Step S4002: If there are at least two simulated detection paths with the same required flight distance and the smallest required flight distance, the simulated detection path corresponding to the smallest required flight distance is defined as the candidate detection path.

[0122] When there are at least two simulation detection paths with the same and minimum required flight distance, it means that there are multiple simulation detection paths that meet the requirements. At this time, they are defined as alternative detection paths to distinguish different simulation detection paths, which facilitates the subsequent determination of the only detection path to be used.

[0123] Step S401: defining a valid area in the candidate detection path where the ratio of the duration interval is greater than the preset ratio of the boundary interval as a high-value area.

[0124] The boundary interval ratio is the minimum interval ratio set by the staff to determine that the value of testing the valid area is relatively high. By defining high-value areas, areas that are quite worth testing can be determined to facilitate subsequent analysis.

[0125] Step S402: Count the high-value areas to determine the high-value quantity, determine the high-value quantity with the largest value according to the sorting rule, and define the alternative detection path corresponding to the high-value quantity as the used detection path.

[0126] The high-value number is the total number of high-value areas determined. The high-value number with the largest value is determined to indicate that the corresponding alternative detection path is most suitable for the drone to perform mobile operations. At this time, it can be determined as the detection path to be used.

[0127] After acquiring the dam inspection image, the dam inspection method based on drone also includes:

[0128] Step S500: performing feature recognition based on the dam detection image to determine the dam crack characteristics.

[0129] The characteristics of dam cracks are the characteristics of obvious cracks on the dam that need to be repaired. The feature recognition method can be used to build a recognition database through sample learning in advance, and then the current dam detection image is input into the recognition database to identify and determine the crack characteristics.

[0130] Step S501: Determine whether the dam crack feature has an intersection with the contour line of the local area corresponding to the dam detection image.

[0131] The purpose of the judgment is to find out whether the currently determined crack characteristics are likely to extend to other local areas.

[0132] Step S5011: If the dam crack feature does not intersect with the contour line of the local area corresponding to the dam detection image, a detection completion signal is output.

[0133] When the dam crack feature does not intersect with the contour line of the local area corresponding to the dam detection image, it means that all the determined crack features are extended to the remaining local areas, that is, the current detection is completed. At this time, the detection completion signal can be output to identify the situation.

[0134] Step S5012: If there is an intersection between the dam crack feature and the contour line of the local area corresponding to the dam detection image, the local area with the intersection on the remaining contour lines is defined as the area to be tested.

[0135] When there is an intersection between the dam crack feature and the contour line of the local area corresponding to the dam detection image, it means that the crack feature extends to the remaining local area. At this time, it is determined as the area to be tested to distinguish different local areas, which is convenient for subsequent analysis.

[0136] Step S502: The area to be tested that is neither the required detection area nor the effective area is defined as a secondary area, and a secondary operation path is constructed based on the secondary area, and the UAV is controlled to move along the secondary operation path to obtain the dam detection image again.

[0137] When the area to be tested is neither the required detection area nor the valid area, it means that the area to be tested needs to be tested. At this time, it is defined as a secondary area for identification to facilitate subsequent analysis; the secondary operation path is the flight path that the drone can take to perform detection operations on each secondary area. The method for determining this path is consistent with the above-mentioned detection path and will not be repeated here; by controlling the drone to move along the secondary operation path, the crack conditions in the remaining local areas can continue to be detected. If a secondary area is still determined later, the detection can continue until the detection completion signal is output.

[0138] After the secondary area is determined, the drone-based embankment inspection method also includes:

[0139] Step S600: defining the effective area where the dam crack features exist as a crack area.

[0140] The crack area is defined to identify the effective area where embankment crack characteristics exist, which is convenient for subsequent analysis.

[0141] Step S601: defining the time interval ratio corresponding to the crack area as the crack existence ratio.

[0142] The crack existence ratio is defined to distinguish the ratios of different time intervals for the convenience of subsequent analysis.

[0143] Step S602: randomly selecting a crack existence ratio as the center existence ratio, and constructing a similar ratio range according to the center existence ratio and a preset similar ratio.

[0144] The similar proportion is the maximum difference allowed when the two crack existence proportion values ​​set by the staff are relatively close. The similar proportion range is the range allowed for the existence proportions of other cracks that are close to the center existence proportion. This range is determined by adding and subtracting the similar proportion to the center existence proportion.

[0145] Step S603: Count the crack existence ratios within a similar range to determine the internal existence quantity, and count all crack existence ratios to determine the overall existence quantity.

[0146] The internal existence quantity is the total amount of data on the crack existence ratio that is within a similar range to the determined ratio, and the overall existence quantity is the total amount of data on the determined crack existence ratio.

[0147] Step S604: Calculate the internal quantity ratio based on the internal quantity and the overall quantity.

[0148] The internal quantity ratio is the ratio of the data volume of the crack existence ratio within a similar range to the data volume of all crack existence ratios, and is determined by dividing the internal existence quantity by the overall existence quantity.

[0149] Step S605: Determine whether there is a situation where the internal quantity ratio is greater than the preset aggregation quantity ratio.

[0150] The aggregation ratio is the minimum internal ratio set by the staff to determine that a large number of cracks exist and must be aggregated. The purpose of the judgment is to understand the specific situation of the currently detected effective area.

[0151] Step S6051: If there is no situation where the internal quantity ratio is greater than the aggregate quantity ratio, the currently determined secondary area is maintained.

[0152] When there is no situation where the proportion of internal quantity is greater than the proportion of aggregate quantity, it means that there is no collective proportional change in the effective area, that is, it is impossible to determine the area that needs to be detected subsequently through the first detection. At this time, the determined secondary area can be maintained normally.

[0153] Step S6052: If there is a situation where the internal quantity ratio is greater than the aggregate quantity ratio, the crack existence ratio within a similar range corresponding to the internal quantity ratio with the largest value is averaged to determine the advance average ratio.

[0154] When the proportion of internal number is greater than the proportion of aggregated number, it means that there are a large number of cracks with an aggregated proportion, that is, the cracks in the dam are all in advance in equal proportion. At this time, the average proportion of advance can be obtained by calculating the average value.

[0155] Step S606: Determine a local area whose average advance ratio is greater than the corresponding time interval ratio and is neither a demand detection area nor a valid area as a secondary area.

[0156] When the average advance ratio is greater than the corresponding time interval ratio, it indicates that the local area also has a high risk of cracks. Therefore, it is also determined as a secondary area for detection, so that the second detection can cover the area with cracks as much as possible.

[0157] After the detection signal is output, the dam inspection method based on drones also includes:

[0158] Step S700: Obtain the number of detection areas and the number of abnormal areas.

[0159] The number of detection areas is the number of local areas that are fully detected during the overall detection process of the UAV, and the number of abnormal areas is the number of areas detected with crack characteristics.

[0160] Step S701: Calculate the abnormal detection ratio based on the number of detection areas and the number of abnormal areas.

[0161] The abnormal detection ratio is the ratio of the detected areas with crack characteristics, which is determined by dividing the number of abnormal areas by the number of detected areas.

[0162] Step S702: Determine the detection evaluation coefficient corresponding to the abnormal detection ratio according to the preset evaluation matching relationship.

[0163] The detection evaluation coefficient is a parameter value that reflects the detection effect of the current detection. The larger the value, the more valuable the current detection is. The larger the proportion of abnormal detection, the stronger the necessity of the detection at this time, that is, the larger the detection evaluation coefficient, and the staff can subsequently use the detection evaluation coefficient to determine the detection situation.

[0164] Reference Figure 2 Based on the same inventive concept, an embodiment of the present invention provides a dam inspection system based on a drone, comprising:

[0165] An acquisition module is used to obtain regional detection time points of each preset local area on the dam;

[0166] A processing module, connected to the acquisition module, for storing and processing information;

[0167] The processing module determines the detection interval duration based on the regional detection time point and the current time point;

[0168] The processing module constructs a historical interval with the current time point as the end point and a width of the preset historical length on the preset time axis, and obtains the crack interval length of each local area in the historical interval;

[0169] The processing module calculates the effective interval duration based on all crack interval durations in a single local area, and defines the local area where the detection interval duration is longer than the effective interval duration as the required detection area;

[0170] The processing module determines regional detection points on the required detection area, randomly sorts the regional detection points, and connects them in series with a preset starting point to construct a simulated detection path, and determines the required flight distance based on the simulated detection path;

[0171] The processing module determines the minimum required flight distance according to a preset sorting rule, defines the simulated inspection path corresponding to the required flight distance as the used inspection path, and controls the UAV to move along the used inspection path from the starting point to obtain dam inspection images;

[0172] An effective interval duration determination module is used to determine an appropriate effective interval duration for data analysis;

[0173] The required flight distance update module updates the required flight distance according to the incidental detection results during the UAV flight;

[0174] A simulation detection path screening module is used to screen multiple simulation detection paths that meet the requirements;

[0175] A secondary detection control module is used to determine the path of the drone's secondary detection to control the drone's operation;

[0176] Secondary area adding module, which adds secondary areas according to the specific conditions of each local area;

[0177] The test result evaluation module is used to evaluate the overall test status of the dam.

[0178] Those skilled in the art will clearly understand that for the sake of convenience and brevity, the division of the above-mentioned functional modules is only used as an example for illustration. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working processes of the above-mentioned systems, devices, and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

Claims

1. A dam inspection method based on drone, characterized in that: include: Obtaining regional detection time points of each preset local area on the dam; Determine the detection interval length based on the regional detection time point and the current time point; Construct a historical interval on a preset time axis with the current time point as the end point and a width of a preset historical length, and obtain the crack interval duration of each local area in the historical interval; In a single local area, the effective interval duration is calculated based on all crack interval durations, and the local area where the detection interval duration is longer than the effective interval duration is defined as the area requiring detection; Determine regional detection points in the required detection area, randomly sort the regional detection points, and connect them in series with a preset starting point to construct a simulated detection path, and determine the required flight distance based on the simulated detection path; Determine the minimum required flight distance according to a preset sorting rule, define the simulated inspection path corresponding to the required flight distance as the used inspection path, and control the UAV to move along the used inspection path from the starting point to obtain dam inspection images; The steps for calculating the effective interval duration based on all crack interval durations in a single local area include: Obtain the crack determination time point corresponding to the crack interval duration; Determine the data interval length based on the crack determination time point and the current time point, and define the data interval length with the smallest value as the benchmark interval length; Calculate the extension ratio based on the data interval and the benchmark interval; Determine the relative reliability coefficient corresponding to the extension ratio according to the preset reliable matching relationship, and calculate the reliable calculation weight corresponding to each crack interval length according to each relative reliability coefficient; The simulation interval is determined by calculating the interval length of each crack and the corresponding reliable calculation weight; Determine whether the simulation interval is greater than the preset fixed interval; If the simulation interval duration is not greater than the fixed interval duration, the simulation interval duration is determined as the effective interval duration; If the simulation interval duration is greater than the fixed interval duration, the fixed interval duration is determined as the effective interval duration.

2. The dam inspection method based on drone according to claim 1 is characterized in that: After the required flight distance is determined, the drone-based dam inspection method also includes: The local area that is not the required detection area is defined as the waiting area; Determine the detection coverage area based on the current simulated detection path and the preset unit coverage area; The area within the detection coverage area of ​​a single waiting area is defined as an incidental area, and the incidental ratio is determined based on the incidental area and the waiting area. The waiting area whose incidental ratio is greater than the preset effective detection ratio is defined as an effective area; The duration interval ratio is determined by calculating the duration of the detection interval in the effective area and the duration of the effective interval; Determine the simulated distance reduction corresponding to the time interval ratio based on the preset candidate matching relationship, and sum up all the simulated distance reductions to determine the overall distance reduction; The required flight distance is updated by performing a difference calculation based on the overall reduction distance and the required flight distance.

3. The dam inspection method based on drone according to claim 2, characterized in that: After the required flight path is updated, the drone-based dam inspection method also includes: Determine whether there are at least two simulated detection paths with the same required flight distance and the minimum required flight distance; If there are not at least two simulated detection paths with the same required flight distance and the minimum required flight distance, the simulated detection path corresponding to the minimum required flight distance is defined as the used detection path; If there are at least two simulated detection paths with the same required flight distance and the smallest required flight distance, the simulated detection path corresponding to the smallest required flight distance is defined as the alternative detection path; In the alternative detection path, the effective area where the ratio of the time interval is greater than the preset ratio of the boundary interval is defined as a high-value area; The high-value areas are counted to determine the high-value quantity, and the high-value quantity with the largest value is determined according to the sorting rule, and the alternative detection path corresponding to the high-value quantity is defined as the detection path to be used.

4. The dam inspection method based on drone according to claim 3 is characterized in that: After acquiring the dam inspection image, the dam inspection method based on drone also includes: Perform feature recognition based on the dam inspection image to determine the dam crack characteristics; Determine whether the dam crack feature has an intersection with the contour line of the local area corresponding to the dam detection image; If the crack feature of the dam does not intersect with the contour line of the local area corresponding to the dam detection image, a detection completion signal is output; If there is an intersection between the dam crack feature and the contour line of the local area corresponding to the dam detection image, the local area with the intersection on the remaining contour lines is defined as the area to be tested; The area to be tested that is not the required detection area and the effective area is defined as a secondary area, and a secondary operation path is constructed based on the secondary area, and the UAV is controlled to move along the secondary operation path to obtain the embankment detection image again.

5. The dam inspection method based on drone according to claim 4 is characterized in that: After the secondary area is determined, the drone-based embankment inspection method also includes: The effective area where embankment crack characteristics exist is defined as the crack area; The proportion of time intervals corresponding to the crack area is defined as the crack existence proportion; Randomly select a crack existence ratio as the center existence ratio, and construct a similar ratio range based on the center existence ratio and the preset similar ratio; Count the proportions of cracks within a similar range to determine the number of cracks present inside, and count all the cracks to determine the overall number of cracks present. Calculate the internal quantity and the overall quantity to determine the internal quantity ratio; Determine whether the internal quantity ratio is greater than the preset aggregate quantity ratio; If there is no situation where the proportion of internal quantity is greater than the proportion of aggregate quantity, the currently determined secondary area is maintained; If the proportion of internal quantity is greater than the proportion of aggregate quantity, the proportion of cracks in the range close to the maximum internal quantity proportion will be averaged to determine the advance average proportion. The local area whose average advance ratio is greater than the corresponding time interval ratio and is not a demand detection area or a valid area is determined as a secondary area.

6. The dam inspection method based on drone according to claim 5, characterized in that: After the detection signal is output, the dam inspection method based on drones also includes: Get the number of detected areas and the number of abnormal areas; Calculate the abnormal detection ratio based on the number of detection areas and the number of abnormal areas; The detection evaluation coefficient corresponding to the abnormal detection ratio is determined based on the preset evaluation matching relationship.

7. A dam inspection system based on drones, characterized in that: include: An acquisition module is used to obtain regional detection time points of each preset local area on the dam; A processing module, connected to the acquisition module, for storing and processing information; The processing module determines the detection interval duration based on the regional detection time point and the current time point; The processing module constructs a historical interval with the current time point as the end point and a width of the preset historical length on the preset time axis, and obtains the crack interval length of each local area in the historical interval; The processing module calculates the effective interval duration based on all crack interval durations in a single local area, and defines the local area where the detection interval duration is longer than the effective interval duration as the required detection area; The processing module determines regional detection points on the required detection area, randomly sorts the regional detection points, and connects them in series with a preset starting point to construct a simulated detection path, and determines the required flight distance based on the simulated detection path; The processing module determines the minimum required flight distance according to a preset sorting rule, defines the simulated inspection path corresponding to the required flight distance as the used inspection path, and controls the UAV to move along the used inspection path from the starting point to obtain dam inspection images; The steps for calculating the effective interval duration based on all crack interval durations in a single local area include: The acquisition module acquires the crack determination time point corresponding to the crack interval duration; The processing module determines the data interval length according to the crack determination time point and the current time point, and defines the data interval length with the smallest value as the benchmark interval length; The processing module calculates the extension ratio based on the data interval and the benchmark interval; The processing module determines the relative reliability coefficient corresponding to the extension ratio according to the preset reliable matching relationship, and calculates the reliability calculation weight corresponding to each crack interval length according to each relative reliability coefficient; The processing module calculates the simulation interval length according to the interval length of each crack and the corresponding reliable calculation weight; The processing module determines whether the simulation interval duration is greater than the preset fixed interval duration; If the simulation interval duration is not greater than the fixed interval duration, the processing module determines the simulation interval duration as the effective interval duration; If the simulation interval duration is greater than the fixed interval duration, the processing module determines the fixed interval duration as the effective interval duration.

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