Method and device for detecting water storage state of a slag pool

Abstract

The application discloses a kind of detection method and device of the water storage state of flushing slag pool, it is related to flushing slag pool water detection technical field, wherein the method comprises: obtaining the three-dimensional data of flushing slag pool;The three-dimensional data is obtained after scanning flushing slag pool using laser radar;The three-dimensional data is preprocessed, and the three-dimensional point cloud data of flushing slag pool is obtained, and the three-dimensional point cloud data includes three-dimensional point cloud coordinate data;According to the quantity of three-dimensional point cloud data and three-dimensional point cloud coordinate data, the water storage state of flushing slag pool is detected.The application can solve the problems of waste of human resources, inaccurate judgment result of the water storage state of flushing slag pool, low production efficiency, high energy consumption and large equipment loss in the prior art.

Description

Technical Field

[0001] This invention relates to the field of water storage detection technology in slag flushing tanks, and in particular to a method and apparatus for detecting the water storage status of slag flushing tanks. Background Technology

[0002] This section is intended to provide background or context for the embodiments of the invention set forth in the claims. The description herein is not an admission that it is prior art simply because it is included in this section.

[0003] A slag flushing tank is a bucket-shaped concrete structure, wider at the top and narrower at the bottom, used to collect blast furnace slag. In the metallurgical industry, blast furnace smelting produces a large amount of slag. After being granulated by high-speed water quenching, the slag enters the slag flushing tank. The large amount of slag settling at the bottom of the tank can easily lead to poor water permeability, affecting the operation of related pumps and even disrupting normal blast furnace production. Furthermore, the water-quenched slag is a high-quality cement raw material. Therefore, in actual production, the slag needs to be continuously removed from the slag flushing tank, and overhead cranes are one of the most important slag removal devices.

[0004] As the drawbacks of traditional overhead crane systems become increasingly apparent, more and more systems are being upgraded to unmanned overhead crane systems. The operating methods of unmanned overhead cranes are mainly divided into sequential methods and three-dimensional positioning methods. The three-dimensional positioning method has a higher degree of intelligence and wider application, but it also has stricter requirements for operating conditions. LiDAR is a crucial detection device in the three-dimensional positioning method. However, water absorbs laser energy. When there is water in the slag flushing tank, it severely affects the detection results, leading to positioning algorithm errors, and consequently, slag removal with water or slag removal failure. Frequent slag removal with water or slag removal failure will reduce work efficiency, increase energy consumption, and also increase equipment wear and tear. Therefore, the water status of the slag flushing tank needs to be monitored when the unmanned overhead crane is operating.

[0005] In existing technologies, the detection of water status in slag flushing tanks mainly includes two methods. One is manual confirmation, which involves installing cameras at appropriate locations to monitor the status of the slag flushing tank in real time. Staff members confirm the current water status of the slag flushing tank through video monitoring. If there is no water, a command is sent to activate the unmanned overhead crane system; if there is water, a command is sent to temporarily disable the unmanned overhead crane system. This method requires at least one staff member to observe and monitor the tank for an extended period, resulting in high human resource costs, and manual confirmation carries the risk of misjudgment. Another method is the waiting method. The water in the slag flushing tank flows into the tank during slag flushing. The inflow of water can be estimated based on the duration of slag flushing, and the outflow of water per unit time can be estimated based on the permeability of the slag and the power of the bottom pump. The outflow time can be calculated by multiplying the inflow by the outflow per unit time. That is, a signal is sent to the unmanned crane system at the beginning of each slag flushing. The unmanned crane system delays for a certain period of time before starting the operation to ensure that there is no water in the slag flushing tank. This method requires calculating the outflow of water per unit time based on the permeability of the slag and the power of the bottom pump. However, in long-term use, the permeability will deteriorate and the pump power will fluctuate, resulting in a large error in the calculation results. The calculated waiting time is inaccurate. If the waiting time is too short, the operation will be carried out with water. If the waiting time is too long, the work efficiency will be reduced.

[0006] In summary, existing technologies suffer from problems such as wasted human resources, inaccurate judgment of the water status in the slag pool, low production efficiency, high energy consumption, and significant equipment wear and tear. Summary of the Invention

[0007] This invention provides a method for detecting the water state of a slag flushing tank, addressing the problems of wasted human resources, inaccurate judgment of the water state, low production efficiency, high energy consumption, and significant equipment wear and tear in existing technologies. The method includes:

[0008] Three-dimensional data of the slag flushing pool is obtained; the three-dimensional data is obtained by scanning the slag flushing pool using lidar.

[0009] The three-dimensional data is preprocessed to obtain three-dimensional point cloud data of the slag flushing pool, and the three-dimensional point cloud data includes three-dimensional point cloud coordinate data.

[0010] The water storage status of the slag flushing pool is detected based on the quantity and coordinates of the 3D point cloud data.

[0011] This invention also provides a device for detecting the water status of a slag flushing tank, to solve the problems of wasted human resources, inaccurate judgment of the water status of the slag flushing tank, low production efficiency, high energy consumption, and large equipment wear and tear in the prior art. The device includes:

[0012] The data acquisition module is used to acquire three-dimensional data of the slag flushing pool; the three-dimensional data is obtained by scanning the slag flushing pool using a lidar.

[0013] The first data processing module is used to preprocess the three-dimensional data to obtain three-dimensional point cloud data of the slag flushing pool, wherein the three-dimensional point cloud data includes three-dimensional point cloud coordinate data.

[0014] The second data processing module is used to detect the water storage status of the slag flushing pool based on the quantity and coordinate data of the three-dimensional point cloud data.

[0015] This invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the above-mentioned method for detecting the water status of the slag flushing tank.

[0016] This invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the above-described method for detecting the water status of the slag flushing tank.

[0017] This invention also provides a computer program product, which includes a computer program that, when executed by a processor, implements the above-mentioned method for detecting the water status of the slag flushing tank.

[0018] In this embodiment of the invention, three-dimensional data of the slag flushing pool is acquired. This three-dimensional data is obtained by scanning the pool using a lidar sensor. The three-dimensional data is preprocessed to obtain three-dimensional point cloud data of the slag flushing pool, including three-dimensional point cloud coordinate data. Based on the quantity and coordinates of the three-dimensional point cloud data, the water storage status of the slag flushing pool is detected. Compared to existing methods of manually confirming or waiting to detect the water storage status in the slag flushing pool, this invention obtains three-dimensional point cloud data of the pool through laser scanning. Utilizing the characteristics of water absorbing laser energy and water mist reflecting laser light, the three-dimensional point cloud data is analyzed to determine the water storage status of the slag flushing pool. This solves the problems of wasted human resources, inaccurate judgment of the water storage status, low production efficiency, high energy consumption, and significant equipment wear and tear in existing technologies. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In the drawings:

[0020] Figure 1 This is a flowchart of a method for detecting the water status of a slag flushing tank provided in an embodiment of the present invention;

[0021] Figure 2 This is a schematic diagram of three-dimensional point cloud data formed in a water-free state as provided in an embodiment of the present invention.

[0022] Figure 3 This is a schematic diagram of three-dimensional point cloud data formed in a state with water storage but no water mist, as provided in an embodiment of the present invention.

[0023] Figure 4 This is a schematic diagram of three-dimensional point cloud data formed by a thin water mist state provided in an embodiment of the present invention.

[0024] Figure 5 This is a schematic diagram of three-dimensional point cloud data formed by a state of concentrated water mist with water retention, provided in an embodiment of the present invention.

[0025] Figure 6 This is a schematic diagram of a device for detecting the water status of a slag flushing tank provided in an embodiment of the present invention;

[0026] Figure 7 This is a schematic diagram showing the installation location of the data acquisition module provided in an embodiment of the present invention;

[0027] Figure 8 This is a schematic diagram of the workflow of the method for detecting the water status of the slag flushing tank provided in this embodiment of the invention;

[0028] Figure 9 This is a schematic diagram of a computer device provided in an embodiment of the present invention. Detailed Implementation

[0029] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings. Here, the illustrative embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0030] In the description of this specification, the terms "comprising," "including," "having," and "containing" are open-ended terms, meaning that they include but are not limited to. The terms "an embodiment," "a specific embodiment," "some embodiments," and "for example," etc., refer to specific features, structures, or characteristics described in connection with that embodiment or example that are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, or characteristics described can be combined in any suitable manner in one or more embodiments or examples. The order of steps involved in the various embodiments is used to illustrate the implementation of this application, and the order of steps is not limited and can be adjusted appropriately as needed.

[0031] Research has found that existing technologies for detecting the water state in flushing slag tanks mainly include two methods:

[0032] One method involves manual verification. This is achieved by installing cameras at appropriate locations to monitor the status of the slag flushing pool in real time and transmitting the image information to the control room. When slag removal is required, staff check the water level in the slag flushing pool using the video surveillance images. If there is no water, staff send instructions to the unmanned overhead crane system to automatically grab and unload slag based on the 3D information of the slag pile. If there is water, staff send instructions to the unmanned overhead crane system to operate in another slag flushing pool that meets the work requirements or wait for the water level to drop before operating. This method requires at least one staff member to observe and monitor the pool for an extended period, which is a serious waste given the increasing cost of human resources. Furthermore, since the unmanned overhead crane operates 24 hours a day, manually verifying the water level in the slag flushing pool at night carries a high risk of misjudgment.

[0033] Another method is the waiting method. The water in the slag flushing tank flows into the tank during slag flushing. The inflow of water can be estimated based on the duration of slag flushing, and the outflow of water per unit time can be estimated based on the permeability of the slag and the power of the bottom pump. The outflow time can be calculated by multiplying the inflow by the outflow per unit time. That is, a signal is sent to the unmanned crane system at the beginning of each slag flushing. The unmanned crane system delays for a certain period of time before starting the operation to ensure that there is no water in the slag flushing tank. This method requires calculating the outflow of water per unit time based on the permeability of the slag and the power of the bottom pump. However, in long-term use, the permeability will deteriorate and the pump power will fluctuate, resulting in a large error in the calculation results. The calculated waiting time is inaccurate. If the waiting time is too short, the operation will be carried out with water. If the waiting time is too long, the work efficiency will be reduced.

[0034] In summary, existing technologies suffer from problems such as wasted human resources, inaccurate judgment of the water status in the slag pool, low production efficiency, high energy consumption, and significant equipment wear and tear.

[0035] In response to the above research, this invention proposes a method and device for detecting the water status of a slag flushing tank, which can solve the problems of wasted human resources, inaccurate judgment of the water status of the slag flushing tank, low production efficiency, high energy consumption and large equipment wear and tear in the prior art.

[0036] Figure 1 A flowchart of a method for detecting the water state in a slag flushing tank, provided by an embodiment of the present invention, is included in the following steps:

[0037] Step 101: Obtain three-dimensional data of the slag flushing tank; the three-dimensional data is obtained by scanning the slag flushing tank using a lidar.

[0038] Step 102: Preprocess the three-dimensional data to obtain three-dimensional point cloud data of the slag flushing pool, wherein the three-dimensional point cloud data includes three-dimensional point cloud coordinate data.

[0039] Step 103: Detect the water storage status of the slag flushing pool based on the quantity and coordinate data of the three-dimensional point cloud data.

[0040] In this embodiment of the invention, three-dimensional data of the slag flushing pool is acquired. This three-dimensional data is obtained by scanning the pool using a lidar sensor. The three-dimensional data is preprocessed to obtain three-dimensional point cloud data of the slag flushing pool, including three-dimensional point cloud coordinate data. Based on the quantity and coordinates of the three-dimensional point cloud data, the water storage status of the slag flushing pool is detected. Compared to existing methods of manually confirming or waiting to detect the water storage status in the slag flushing pool, this invention obtains three-dimensional point cloud data of the pool through laser scanning. Utilizing the characteristics of water absorbing laser energy and water mist reflecting laser light, the three-dimensional point cloud data is analyzed to determine the water storage status of the slag flushing pool. This solves the problems of wasted human resources, inaccurate judgment of the water storage status, low production efficiency, high energy consumption, and significant equipment wear and tear in existing technologies.

[0041] The following is combined Figure 1 The method for detecting the water status of the slag flushing tank is explained in detail.

[0042] In step 101 above, three-dimensional data of the slag flushing pool is obtained; the three-dimensional data is obtained by scanning the slag flushing pool using a lidar.

[0043] In practice, lidar can be used to scan the slag flushing pool to obtain three-dimensional data. This three-dimensional data is a point dataset (i.e., point cloud) of the slag flushing pool surface collected by lidar.

[0044] In step 102 above, the three-dimensional data needs to be preprocessed to obtain the three-dimensional point cloud data of the slag flushing pool.

[0045] Among them, 3D point cloud data includes 3D point cloud coordinate data.

[0046] In practice, preprocessing of 3D data can include point cloud formatting, point cloud data calibration, point cloud data segmentation, point cloud data filtering, and so on.

[0047] In one embodiment, step 102, which involves formatting the 3D data into a point cloud, may specifically include:

[0048] Generate point cloud data messages based on 3D data;

[0049] The position coordinate information is added to the point cloud data message according to the scanning order of the lidar to obtain three-dimensional point cloud data.

[0050] In practice, the point cloud formatting of 3D data involves generating a standard point cloud data message based on the 3D data information, and then adding the position coordinate information according to the scanning order to obtain complete 3D point cloud data, thus completing the point cloud formatting process of the 3D data.

[0051] In one embodiment, after obtaining the 3D point cloud data, data calibration of the 3D point cloud data may specifically include:

[0052] Based on the pre-acquired feature point coordinate data of the slag flushing pool, the grab bucket of the unmanned overhead crane is moved to the position corresponding to the feature point coordinate data to determine the coordinate data of the unmanned overhead crane.

[0053] Based on the coordinate data of the unmanned overhead crane, the 3D point cloud data is calibrated.

[0054] In practice, point cloud data calibration first involves selecting a feature point in the slag flushing pool and determining its coordinate data. Then, the grab bucket of the unmanned overhead crane is moved to the feature point, and the coordinate data of the unmanned overhead crane is read. Finally, by performing translation and rotation transformations on the three-dimensional point cloud data, the coordinates of the three-dimensional point cloud data and the unmanned overhead crane are made to coincide, thus achieving data calibration.

[0055] In one embodiment, after data calibration of the 3D point cloud data, data segmentation of the 3D point cloud data may specifically include:

[0056] Based on the coordinate data of the unmanned overhead crane, determine the operating range data of the unmanned overhead crane;

[0057] Based on the operating range data of the unmanned overhead crane and the pre-acquired feature point coordinate data of the slag flushing pool, invalid data in the 3D point cloud data after data calibration is removed.

[0058] In practice, point cloud data segmentation involves selecting a reasonable data range based on the characteristics of the slag flushing pool and the operating range of the unmanned overhead crane system, removing invalid data to optimize display and improve calculation speed. Specifically, the operating range of the unmanned overhead crane is determined based on its coordinate data. Then, based on the operating range data of the unmanned overhead crane and the coordinate data of the feature points of the slag flushing pool, invalid data in the 3D point cloud data is removed.

[0059] In one embodiment, after removing invalid data from the 3D point cloud data, data filtering of the 3D point cloud data may specifically include:

[0060] Point cloud filtering is performed on the 3D point cloud data after removing invalid data to delete discrete points in the 3D point cloud data.

[0061] In practice, point cloud data filtering uses data statistical algorithms to remove discrete points. First, the average value and standard deviation of the distance between all points in a specified neighborhood of any point are calculated. A multiple of the standard deviation is set as a threshold. If the absolute value of the difference between the distance between the point and the average value is greater than the set threshold multiplied by the standard deviation, the point is a discrete point. Filtering is achieved by deleting discrete points to reduce noise interference.

[0062] After preprocessing the three-dimensional data using the above preprocessing method, three-dimensional point cloud data of the slag flushing pool is obtained. This three-dimensional point cloud data includes three-dimensional point cloud coordinate data.

[0063] In one embodiment, the three-dimensional point cloud coordinate data includes length coordinates, width coordinates, and height coordinates; the direction of the length coordinates is parallel to the long side of the slag flushing pool, the direction of the width coordinates is parallel to the short side of the slag flushing pool, and the direction of the height coordinates is parallel to the perpendicular line of the slag flushing pool.

[0064] It is understandable that the three-dimensional point cloud coordinate data of each three-dimensional point cloud data consists of three data points: x (length coordinate), y (width coordinate), and z (height coordinate). The x-coordinate is parallel to the long side of the slag flushing pool, the y-coordinate is parallel to the short side of the slag flushing pool, and the z-coordinate is parallel to the vertical line.

[0065] In step 103 above, the water storage status of the slag flushing pool is detected based on the quantity and coordinate data of the three-dimensional point cloud data.

[0066] In practice, a pre-set water storage detection algorithm can be used to analyze the quantity and coordinates of the 3D point cloud data to determine the water storage status of the slag flushing tank. Specifically, the water storage detection algorithm utilizes the characteristics of water absorbing laser energy and the characteristics of water mist reflecting laser light to determine the water storage status within the slag flushing tank.

[0067] In one embodiment, step 103 may specifically include:

[0068] Based on the 3D point cloud coordinate data, determine the maximum value, minimum value, range, and standard deviation of the elevation coordinate in the 3D point cloud coordinate data.

[0069] The water storage status of the slag flushing pool is determined based on the quantity of 3D point cloud data, the maximum value of the elevation coordinate in the 3D point cloud coordinate data, the range of the elevation coordinate in the direction of the elevation coordinate, and the standard deviation of the elevation coordinate in the direction of the elevation coordinate.

[0070] In practice, the maximum value p of the height coordinate is determined based on the coordinate data (x, y, z) of all 3D point cloud data. max .z, that is, determining the maximum value in the z-direction among all 3D point cloud data p; and determining the minimum value p of the height coordinate. min .z, that is, determining the minimum value in the z-direction among all 3D point cloud data p; based on p max .z and p min .z, determine the range of the height coordinate in the z direction as diff; and determine the standard deviation σ of the height coordinate in the z direction based on all z values ​​in the coordinate data (x, y, z) of the 3D point cloud data.

[0071] For example, the range in the z-direction can be calculated as diff using the following formula:

[0072] diff = p max .zp min .z

[0073] Let the mean value in the z-direction be μ, and calculate the standard deviation σ in the z-direction using the following formula:

[0074]

[0075]

[0076] Where, p i .z represents the z-value of the i-th 3D point cloud data, and n represents the total number of 3D point cloud data.

[0077] In practice, the minimum number of point clouds n for the slag flushing pool can be preset. min The range threshold in the z-direction (the range threshold in the height direction of the slag flushing pool) is diff. th The height threshold in the z-direction (height threshold of the slag flushing pool) is h. th The standard deviation threshold in the z-direction (the standard deviation threshold in the height direction of the slag flushing pool) is σ. th The number of 3D point cloud data, n, p maxz, diff, and σ are compared with their respective thresholds to determine the water storage status of the slag flushing tank.

[0078] In one embodiment, the water storage state of the slag flushing tank is determined based on the quantity of 3D point cloud data, the maximum value of the elevation coordinate in the 3D point cloud coordinate data, the range of the elevation coordinate in the direction of the elevation coordinate, and the standard deviation of the elevation coordinate in the direction of the elevation coordinate. Specifically, this may include:

[0079] If the number of three-dimensional point cloud data is greater than the minimum number of point cloud data in the preset slag flushing pool, and the maximum value of the height coordinate in the three-dimensional point cloud coordinate data is less than the preset height threshold of the slag flushing pool, and the range of the height coordinate in the direction of the three-dimensional point cloud coordinate data is greater than the preset range threshold of the height direction of the slag flushing pool, and the standard deviation of the height coordinate in the direction of the three-dimensional point cloud coordinate data is greater than the preset standard deviation threshold of the height direction of the slag flushing pool, then the water storage status of the slag flushing pool is determined to be no water storage.

[0080] In practice, when there is no water in the slag flushing tank, most of the laser light will be reflected back. At this time, there is a large amount of 3D point cloud data in the slag flushing tank. The highest point of the point cloud is lower than the preset extreme value, and the dispersion in the z-direction is large, so the z-direction range and standard deviation are large. The 3D point cloud data formed in the waterless state is as follows: Figure 2 As shown.

[0081] Therefore, the slag flushing tank is considered to be empty of water when the following conditions are met:

[0082] n>n min

[0083] p max .z <h th

[0084] diff>diff th

[0085] σ>σ th

[0086] In one embodiment, the water storage state of the slag flushing tank is determined based on the quantity of 3D point cloud data, the maximum value of the elevation coordinate in the 3D point cloud coordinate data, the range of the elevation coordinate in the direction of the elevation coordinate, and the standard deviation of the elevation coordinate in the direction of the elevation coordinate, including:

[0087] If the number of 3D point cloud data is less than the preset minimum number of point cloud data for the slag flushing pool, the water storage status of the slag flushing pool is determined to be water storage without water mist.

[0088] In practice, when there is water in the slag flushing tank but no water mist, the water absorbs laser energy, resulting in very low echo energy. Often, only a very small amount of 3D point cloud data is displayed, with most of the data being empty. The 3D point cloud data formed in the state of water storage without water mist is as follows: Figure 3 As shown.

[0089] Therefore, the water state of the slag flushing tank is determined to be water with no water mist when the following conditions are met:

[0090] n <n min

[0091] In one embodiment, the water storage state of the slag flushing tank is determined based on the quantity of 3D point cloud data, the maximum value of the elevation coordinate in the 3D point cloud coordinate data, the range of the elevation coordinate in the direction of the elevation coordinate, and the standard deviation of the elevation coordinate in the direction of the elevation coordinate, including:

[0092] If the maximum value of the height coordinate in the three-dimensional point cloud coordinate data is less than the preset height threshold of the slag flushing pool, and the range of the height coordinate in the direction of the three-dimensional point cloud coordinate data is less than the preset range threshold of the height direction of the slag flushing pool, and the standard deviation of the height coordinate in the direction of the three-dimensional point cloud coordinate data is less than the preset standard deviation threshold of the height direction of the slag flushing pool, then the water storage state of the slag flushing pool is determined to be thin water mist with water storage.

[0093] In practice, the slag flushing tank contains water and a slight water mist. The slight water mist reflects laser energy, resulting in 3D point cloud data that remains largely on the same plane, with its highest point below a set height threshold and very low dispersion. The 3D point cloud data formed in the presence of water and a thin water mist is shown below. Figure 4 As shown.

[0094] Therefore, the water state of the slag flushing tank is determined to be a thin water mist when the following conditions are met:

[0095] p max .z <h th

[0096] diff <diff th

[0097] σ<σ th

[0098] In one embodiment, the water storage state of the slag flushing tank is determined based on the quantity of 3D point cloud data, the maximum value of the elevation coordinate in the 3D point cloud coordinate data, the range of the elevation coordinate in the direction of the elevation coordinate, and the standard deviation of the elevation coordinate in the direction of the elevation coordinate, including:

[0099] If the maximum value of the height coordinate in the three-dimensional point cloud coordinate data is greater than the preset height threshold of the slag flushing pool, and the range of the height coordinate in the direction of the three-dimensional point cloud coordinate data is greater than the preset range threshold of the height direction of the slag flushing pool, and the standard deviation of the height coordinate in the direction of the three-dimensional point cloud coordinate data is greater than the preset standard deviation threshold of the height direction of the slag flushing pool, then the water storage state of the slag flushing pool is determined to be that there is concentrated water mist.

[0100] In practice, the slag flushing tank contains both stored water and concentrated water mist. The concentrated water mist reflects laser energy, resulting in irregularly shaped 3D point cloud data with its highest point exceeding a set height threshold and exhibiting high dispersion. The 3D point cloud data formed in the presence of stored water and concentrated water mist is shown below. Figure 5 As shown.

[0101] Therefore, the water state of the slag flushing tank is determined to be that there is concentrated water mist when the following conditions are met:

[0102] p max .z>h th

[0103] diff>diff th

[0104] σ>σ th

[0105] In summary, based on the above conditions, the water status in the slag flushing tank can be detected.

[0106] In one embodiment, after step 103, the following may also be included:

[0107] The water level in the slag flushing tank is sent to the unmanned overhead crane system so that the unmanned overhead crane system can operate according to the water level in the slag flushing tank.

[0108] In practice, the unmanned overhead crane system operates normally if there is no water in the slag flushing pool, and if there is water, the unmanned overhead crane can go to other slag flushing pools to work or wait for the water level to drop before starting work.

[0109] In one embodiment, after step 103, the following may also be included:

[0110] Display the 3D point cloud data of the slag flushing tank, as well as the water storage status of the tank.

[0111] In practice, a 3D view and key information of the slag flushing pool can be displayed. Specifically, the collected 3D point cloud data of the slag flushing pool and the determined water storage status of the pool can be displayed. After each scan, the 3D point cloud data (3D view of the slag flushing pool) and the corresponding water storage status are updated, allowing staff to have a more intuitive understanding of the slag pile situation. This also facilitates staff monitoring of the system's operating status and timely diagnosis of any problems encountered.

[0112] In this embodiment of the invention, three-dimensional point cloud data is obtained by performing a three-dimensional scan of the slag flushing pool, and then the water storage detection algorithm is used to determine the water storage status in the slag flushing pool. This reduces the risk of unmanned overhead crane systems operating with water, makes the unmanned overhead crane operation mode more reasonable, improves its working efficiency, reduces energy consumption, and reduces the risk of equipment damage.

[0113] This invention also provides a device for detecting the water state of a slag flushing tank, as described in the following embodiments. Since the principle by which this device solves the problem is similar to the method for detecting the water state of a slag flushing tank, the implementation of this device can refer to the implementation of the method for detecting the water state of a slag flushing tank; repeated details will not be elaborated further.

[0114] like Figure 6 The diagram shown is a schematic of a device for detecting the water status of a slag flushing tank according to an embodiment of the present invention. The device may include:

[0115] The data acquisition module 601 is used to acquire three-dimensional data of the slag flushing pool; the three-dimensional data is obtained by scanning the slag flushing pool using a lidar.

[0116] The first data processing module 602 is used to preprocess the three-dimensional data to obtain three-dimensional point cloud data of the slag flushing pool, wherein the three-dimensional point cloud data includes three-dimensional point cloud coordinate data.

[0117] The second data processing module 603 is used to detect the water storage status of the slag flushing pool based on the quantity and coordinate data of the three-dimensional point cloud data.

[0118] In one embodiment, the first data processing module 602 may be specifically used for:

[0119] Generate point cloud data messages based on 3D data;

[0120] The position coordinate information is added to the point cloud data message according to the scanning order of the lidar to obtain three-dimensional point cloud data.

[0121] In one embodiment, the first data processing module 602 may further be used for:

[0122] Based on the pre-acquired feature point coordinate data of the slag flushing pool, the grab bucket of the unmanned overhead crane is moved to the position corresponding to the feature point coordinate data to determine the coordinate data of the unmanned overhead crane.

[0123] Based on the coordinate data of the unmanned overhead crane, the 3D point cloud data is calibrated.

[0124] In one embodiment, the first data processing module 602 may further be used for:

[0125] Based on the coordinate data of the unmanned overhead crane, determine the operating range data of the unmanned overhead crane;

[0126] Based on the operating range data of the unmanned overhead crane and the pre-acquired feature point coordinate data of the slag flushing pool, invalid data in the 3D point cloud data after data calibration is removed.

[0127] In one embodiment, the three-dimensional point cloud coordinate data may include length coordinates, width coordinates, and height coordinates; the direction of the length coordinates is parallel to the long side of the slag flushing pool, the direction of the width coordinates is parallel to the short side of the slag flushing pool, and the direction of the height coordinates is parallel to the perpendicular line of the slag flushing pool.

[0128] The second data processing module 603 can be specifically used for:

[0129] Based on the 3D point cloud coordinate data, determine the maximum value, minimum value, range, and standard deviation of the elevation coordinate in the 3D point cloud coordinate data.

[0130] The water storage status of the slag flushing pool is determined based on the quantity of 3D point cloud data, the maximum value of the elevation coordinate in the 3D point cloud coordinate data, the range of the elevation coordinate in the direction of the elevation coordinate, and the standard deviation of the elevation coordinate in the direction of the elevation coordinate.

[0131] In one embodiment, the second data processing module 603 can also be used for:

[0132] If the number of three-dimensional point cloud data is greater than the minimum number of point cloud data in the preset slag flushing pool, and the maximum value of the height coordinate in the three-dimensional point cloud coordinate data is less than the preset height threshold of the slag flushing pool, and the range of the height coordinate in the direction of the three-dimensional point cloud coordinate data is greater than the preset range threshold of the height direction of the slag flushing pool, and the standard deviation of the height coordinate in the direction of the three-dimensional point cloud coordinate data is greater than the preset standard deviation threshold of the height direction of the slag flushing pool, then the water storage status of the slag flushing pool is determined to be no water storage.

[0133] In one embodiment, the second data processing module 603 can also be used for:

[0134] If the number of 3D point cloud data is less than the preset minimum number of point cloud data for the slag flushing pool, the water storage status of the slag flushing pool is determined to be water storage without water mist.

[0135] In one embodiment, the second data processing module 603 can also be used for:

[0136] If the maximum value of the height coordinate in the three-dimensional point cloud coordinate data is less than the preset height threshold of the slag flushing pool, and the range of the height coordinate in the direction of the three-dimensional point cloud coordinate data is less than the preset range threshold of the height direction of the slag flushing pool, and the standard deviation of the height coordinate in the direction of the three-dimensional point cloud coordinate data is less than the preset standard deviation threshold of the height direction of the slag flushing pool, then the water storage state of the slag flushing pool is determined to be thin water mist with water storage.

[0137] In one embodiment, the second data processing module 603 can also be used for:

[0138] If the maximum value of the height coordinate in the three-dimensional point cloud coordinate data is greater than the preset height threshold of the slag flushing pool, and the range of the height coordinate in the direction of the three-dimensional point cloud coordinate data is greater than the preset range threshold of the height direction of the slag flushing pool, and the standard deviation of the height coordinate in the direction of the three-dimensional point cloud coordinate data is greater than the preset standard deviation threshold of the height direction of the slag flushing pool, then the water storage state of the slag flushing pool is determined to be that there is concentrated water mist.

[0139] In one embodiment, a communication module may also be included, used after the second data processing module 603 detects the water storage status of the slag flushing pool based on the quantity and coordinate data of the three-dimensional point cloud data:

[0140] The water level in the slag flushing tank is sent to the unmanned overhead crane system so that the unmanned overhead crane system can operate according to the water level in the slag flushing tank.

[0141] In one embodiment, it may further include a visualization module, used after the second data processing module 603 detects the water storage status of the slag flushing pool based on the quantity and coordinate data of the three-dimensional point cloud data, and further includes:

[0142] Display the 3D point cloud data of the slag flushing tank, as well as the water storage status of the tank.

[0143] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the following detailed description of the method and apparatus for detecting the water state of the slag flushing tank of the present invention will be provided with a specific example.

[0144] like Figure 7 As shown, the data acquisition module can be installed above the slag flushing tank, and its scanning range must be able to completely cover the slag flushing tank.

[0145] In addition, the first data processing module, the second data processing module, the communication module, and the visualization module are installed inside the industrial control computer and placed in an appropriate area where the condition of the slag flushing pool can be observed. When the data acquisition module receives a work instruction, it uses a lidar to obtain three-dimensional data information of the objects within its scanning range. Then, it transmits the data to the first data processing module through the communication module. The data processing module preprocesses the data, and the second data processing module uses a water storage detection algorithm to determine whether there is water in the slag flushing pool and transmits the detection result to the unmanned overhead crane system, while simultaneously displaying the scanning results.

[0146] The following is combined Figure 8 The workflow of the above-mentioned method for detecting the water status of the slag flushing tank is described in detail.

[0147] 1. Initialize system parameters; this only needs to be done upon first use.

[0148] 2. Wait for the unmanned overhead crane system to send a detection command signal.

[0149] 3. When the communication module receives a detection command signal, it triggers the data acquisition module to scan the slag flushing tank to obtain three-dimensional data; if the communication module does not receive a detection command signal, it continues to wait for a detection command.

[0150] 4. After the data acquisition module finishes scanning, it will send the acquired 3D data to the first data processing module.

[0151] 5. The first data processing module preprocesses the three-dimensional data to obtain the three-dimensional point cloud data of the slag flushing pool.

[0152] 6. The second data processing module uses algorithms to determine the water status in the slag flushing pool based on the three-dimensional point cloud data.

[0153] 7. Send the water status of the slag flushing tank to the unmanned overhead crane system.

[0154] 8. The visualization module displays images and key information of the 3D point cloud data of the slag flushing pool (water status within the slag flushing pool).

[0155] This invention also provides a computer device, such as... Figure 9 The diagram shows a schematic of a computer device in an embodiment of the present invention. The computer device 900 includes a memory 910, a processor 920, and a computer program 930 stored in the memory 910 and executable on the processor 920. When the processor 920 executes the computer program 930, it implements the above-mentioned method for detecting the water status of the slag flushing tank.

[0156] This invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the above-described method for detecting the water status of the slag flushing tank.

[0157] This invention also provides a computer program product, which includes a computer program that, when executed by a processor, implements the above-mentioned method for detecting the water status of the slag flushing tank.

[0158] In this embodiment of the invention, three-dimensional data of the slag flushing pool is acquired. This three-dimensional data is obtained by scanning the pool using a lidar sensor. The three-dimensional data is preprocessed to obtain three-dimensional point cloud data of the slag flushing pool, including three-dimensional point cloud coordinate data. Based on the quantity and coordinates of the three-dimensional point cloud data, the water storage status of the slag flushing pool is detected. Compared to existing methods of manually confirming or waiting to detect the water storage status in the slag flushing pool, this invention obtains three-dimensional point cloud data of the pool through laser scanning. Utilizing the characteristics of water absorbing laser energy and water mist reflecting laser light, the three-dimensional point cloud data is analyzed to determine the water storage status of the slag flushing pool. This solves the problems of wasted human resources, inaccurate judgment of the water storage status, low production efficiency, high energy consumption, and significant equipment wear and tear in existing technologies.

[0159] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0160] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0161] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0162] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0163] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for detecting the water state in a slag flushing tank, characterized in that, include: Obtain three-dimensional data of the slag flushing pool; The three-dimensional data was obtained by scanning the slag flushing pool using lidar; The three-dimensional data is preprocessed to obtain three-dimensional point cloud data of the slag flushing pool. The three-dimensional point cloud data includes three-dimensional point cloud coordinate data. The three-dimensional point cloud coordinate data includes length coordinates, width coordinates and height coordinates. The direction of the length coordinate is parallel to the long side of the slag flushing pool, the direction of the width coordinate is parallel to the short side of the slag flushing pool, and the direction of the height coordinate is parallel to the perpendicular line of the slag flushing pool. The water storage status of the slag flushing pool is detected based on the quantity and coordinate data of the three-dimensional point cloud data. The water storage status of the slag flushing pool is detected based on the quantity and coordinates of the 3D point cloud data, including: Based on the 3D point cloud coordinate data, determine the maximum value of the height coordinate in the 3D point cloud coordinate data. Minimum value of height coordinates , the range (diff) in the direction of the altitude coordinates, and the standard deviation in the direction of the altitude coordinates. σ ; The water storage status of the slag flushing tank is determined based on the number of 3D point cloud data, the maximum value of the elevation coordinates in the 3D point cloud coordinate data, the range of the elevation coordinates in the direction of the elevation coordinates, and the standard deviation of the elevation coordinates in the direction of the elevation coordinates; wherein, the minimum number of point cloud data n for the slag flushing tank is preset. min The range threshold in the z-direction is diff th The height threshold in the z-direction is h. th The standard deviation threshold in the z-direction is σ. th The number of 3D point cloud data, n, diff σ Each is compared with its corresponding threshold to determine the water storage status of the slag flushing tank; the water storage status is no water storage, water storage without water mist, water storage with thin water mist, or water storage with dense water mist.

2. The method as described in claim 1, characterized in that, The three-dimensional data is preprocessed to obtain three-dimensional point cloud data of the slag flushing pool, including: Generate point cloud data messages based on 3D data; The position coordinate information is added to the point cloud data message according to the scanning order of the lidar to obtain three-dimensional point cloud data.

3. The method as described in claim 2, characterized in that, After adding the position coordinate information to the point cloud data message according to the scanning sequence of the LiDAR, the resulting 3D point cloud data also includes: Based on the pre-acquired feature point coordinate data of the slag flushing pool, the grab bucket of the unmanned overhead crane is moved to the position corresponding to the feature point coordinate data to determine the coordinate data of the unmanned overhead crane. Based on the coordinate data of the unmanned overhead crane, the 3D point cloud data is calibrated.

4. The method as described in claim 3, characterized in that, After calibrating the 3D point cloud data based on the coordinate data of the unmanned overhead crane, the following steps are also included: Based on the coordinate data of the unmanned overhead crane, determine the operating range data of the unmanned overhead crane; Based on the operating range data of the unmanned overhead crane and the pre-acquired feature point coordinate data of the slag flushing pool, invalid data in the 3D point cloud data after data calibration is removed.

5. The method as described in claim 1, characterized in that, Based on the quantity of 3D point cloud data, the maximum value of the elevation coordinate in the 3D point cloud coordinate data, the range of the elevation coordinate in the direction of the elevation coordinate, and the standard deviation of the elevation coordinate in the direction of the elevation coordinate, the water storage status of the slag flushing tank is determined, including: If the number of three-dimensional point cloud data is greater than the minimum number of point cloud data in the preset slag flushing pool, and the maximum value of the height coordinate in the three-dimensional point cloud coordinate data is less than the preset height threshold of the slag flushing pool, and the range of the height coordinate in the direction of the three-dimensional point cloud coordinate data is greater than the preset range threshold of the height direction of the slag flushing pool, and the standard deviation of the height coordinate in the direction of the three-dimensional point cloud coordinate data is greater than the preset standard deviation threshold of the height direction of the slag flushing pool, then the water storage status of the slag flushing pool is determined to be no water storage.

6. The method as described in claim 1, characterized in that, Based on the quantity of 3D point cloud data, the maximum value of the elevation coordinate in the 3D point cloud coordinate data, the range of the elevation coordinate in the direction of the elevation coordinate, and the standard deviation of the elevation coordinate in the direction of the elevation coordinate, the water storage status of the slag flushing tank is determined, including: If the number of 3D point cloud data is less than the preset minimum number of point cloud data for the slag flushing pool, the water storage status of the slag flushing pool is determined to be water storage without water mist.

7. The method as described in claim 1, characterized in that, Based on the quantity of 3D point cloud data, the maximum value of the elevation coordinate in the 3D point cloud coordinate data, the range of the elevation coordinate in the direction of the elevation coordinate, and the standard deviation of the elevation coordinate in the direction of the elevation coordinate, the water storage status of the slag flushing tank is determined, including: If the maximum value of the height coordinate in the three-dimensional point cloud coordinate data is less than the preset height threshold of the slag flushing pool, and the range of the height coordinate in the direction of the three-dimensional point cloud coordinate data is less than the preset range threshold of the height direction of the slag flushing pool, and the standard deviation of the height coordinate in the direction of the three-dimensional point cloud coordinate data is less than the preset standard deviation threshold of the height direction of the slag flushing pool, then the water storage state of the slag flushing pool is determined to be thin water mist with water storage.

8. The method as described in claim 1, characterized in that, Based on the quantity of 3D point cloud data, the maximum value of the elevation coordinate in the 3D point cloud coordinate data, the range of the elevation coordinate in the direction of the elevation coordinate, and the standard deviation of the elevation coordinate in the direction of the elevation coordinate, the water storage status of the slag flushing tank is determined, including: If the maximum value of the height coordinate in the three-dimensional point cloud coordinate data is greater than the preset height threshold of the slag flushing pool, and the range of the height coordinate in the direction of the three-dimensional point cloud coordinate data is greater than the preset range threshold of the height direction of the slag flushing pool, and the standard deviation of the height coordinate in the direction of the three-dimensional point cloud coordinate data is greater than the preset standard deviation threshold of the height direction of the slag flushing pool, then the water storage state of the slag flushing pool is determined to be that there is concentrated water mist.

9. The method as described in claim 1, characterized in that, After detecting the water storage status of the slag flushing pool based on the quantity and coordinates of the 3D point cloud data, the following steps are also included: The water level in the slag flushing tank is sent to the unmanned overhead crane system so that the unmanned overhead crane system can operate according to the water level in the slag flushing tank.

10. The method as described in claim 1, characterized in that, After detecting the water storage status of the slag flushing pool based on the quantity and coordinates of the 3D point cloud data, the following steps are also included: Display the 3D point cloud data of the slag flushing tank, as well as the water storage status of the tank.

11. A device for detecting the water status of a slag flushing tank, characterized in that, include: The data acquisition module is used to acquire three-dimensional data of the slag flushing pool; The three-dimensional data was obtained by scanning the slag flushing pool using lidar; The first data processing module is used to preprocess the three-dimensional data to obtain three-dimensional point cloud data of the slag flushing pool. The three-dimensional point cloud data includes three-dimensional point cloud coordinate data. The three-dimensional point cloud coordinate data includes length coordinates, width coordinates and height coordinates. The direction of the length coordinate is parallel to the long side of the slag flushing pool, the direction of the width coordinate is parallel to the short side of the slag flushing pool, and the direction of the height coordinate is parallel to the perpendicular line of the slag flushing pool. The second data processing module is used to detect the water storage status of the slag flushing pool based on the quantity and coordinate data of the three-dimensional point cloud data. The second data processing module is specifically used for: Based on the 3D point cloud coordinate data, determine the maximum value of the height coordinate in the 3D point cloud coordinate data. Minimum value of height coordinates , the range (diff) in the direction of the altitude coordinates, and the standard deviation in the direction of the altitude coordinates. σ ; The water storage status of the slag flushing tank is determined based on the number of 3D point cloud data, the maximum value of the elevation coordinates in the 3D point cloud coordinate data, the range of the elevation coordinates in the direction of the elevation coordinates, and the standard deviation of the elevation coordinates in the direction of the elevation coordinates; wherein, the minimum number of point cloud data n for the slag flushing tank is preset. min The range threshold in the z-direction is diff th The height threshold in the z-direction is h. th The standard deviation threshold in the z-direction is σ. th The number of 3D point cloud data, n, diff σ Each is compared with its corresponding threshold to determine the water storage status of the slag flushing tank; the water storage status is no water storage, water storage without water mist, water storage with thin water mist, or water storage with dense water mist.

12. The apparatus as claimed in claim 11, characterized in that, The second data processing module is also used for: If the number of three-dimensional point cloud data is greater than the minimum number of point cloud data in the preset slag flushing pool, and the maximum value of the height coordinate in the three-dimensional point cloud coordinate data is less than the preset height threshold of the slag flushing pool, and the range of the height coordinate in the direction of the three-dimensional point cloud coordinate data is greater than the preset range threshold of the height direction of the slag flushing pool, and the standard deviation of the height coordinate in the direction of the three-dimensional point cloud coordinate data is greater than the preset standard deviation threshold of the height direction of the slag flushing pool, then the water storage status of the slag flushing pool is determined to be no water storage.

13. The apparatus as claimed in claim 11, characterized in that, The second data processing module is also used for: If the number of 3D point cloud data is less than the preset minimum number of point cloud data for the slag flushing pool, the water storage status of the slag flushing pool is determined to be water storage without water mist.

14. The apparatus as claimed in claim 11, characterized in that, The second data processing module is also used for: If the maximum value of the height coordinate in the three-dimensional point cloud coordinate data is less than the preset height threshold of the slag flushing pool, and the range of the height coordinate in the direction of the three-dimensional point cloud coordinate data is less than the preset range threshold of the height direction of the slag flushing pool, and the standard deviation of the height coordinate in the direction of the three-dimensional point cloud coordinate data is less than the preset standard deviation threshold of the height direction of the slag flushing pool, then the water storage state of the slag flushing pool is determined to be thin water mist with water storage.

15. The apparatus as claimed in claim 11, characterized in that, The second data processing module is also used for: If the maximum value of the height coordinate in the three-dimensional point cloud coordinate data is greater than the preset height threshold of the slag flushing pool, and the range of the height coordinate in the direction of the three-dimensional point cloud coordinate data is greater than the preset range threshold of the height direction of the slag flushing pool, and the standard deviation of the height coordinate in the direction of the three-dimensional point cloud coordinate data is greater than the preset standard deviation threshold of the height direction of the slag flushing pool, then the water storage state of the slag flushing pool is determined to be that there is concentrated water mist.

16. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method of any one of claims 1 to 10.

17. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method of any one of claims 1 to 10.

18. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the method of any one of claims 1 to 10.

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