Detection processing method, system and platform suitable for coke warehouse crane charge level

Abstract

The invention discloses a detection processing method, system and platform suitable for a coke warehouse traveling charge level. The method comprises the following steps: generating and acquiring first data corresponding to a to-be-detected coke warehouse traveling charge level in real time; based on the first data, generating second data corresponding to the first data, and preprocessing the second data in real time to generate corresponding third data; according to the third data, constructing a first model corresponding to the to-be-detected coke warehouse traveling material surface, and based on the first model, generating corresponding fourth data; wherein the fourth data is the charge level detection data of the coke warehouse travelling crane, and the system and the platform corresponding to the method are used for realizing the unmanned operation of the coke warehouse travelling crane. The problems of coke warehouse traveling material level detection, point cloud processing, warehouse area three-dimensional modeling construction and presentation, grabbing point positioning and grabbing safety analysis, warehouse area material volume calculation and material opening material accumulation detection are effectively solved.

Description

Technical Field

[0001] The present invention belongs to the technical field of coal coke depot crane processing, and in particular relates to a method, system and platform for detecting and processing material surfaces of coal coke depot cranes. Background Art

[0002] The coal coke warehouse is an important transfer station for the fuel required for blast furnace production. It is responsible for the storage and transportation of blast furnace metallurgical coke and PCI coal. The materials in and out of the warehouse are handled by double-beam bridge cranes (cranes or overhead cranes) and are manually operated on site. The labor load is high, the dust concentration is high, the pungent odor is heavy, and the working environment is poor. In order to reduce the labor load of on-site workers and improve the working environment, it is necessary to carry out intelligent transformation of the existing crane system to meet the production needs of cost reduction, efficiency improvement and digital management.

[0003] At present, there are many cases of intelligent transformation of coal coke storage cranes in China, but there are still some difficulties to be overcome in order to achieve unmanned operation. The unstable automatic operation also leads to high operation and maintenance costs and low operation performance. Therefore, it is necessary to continuously explore the process technology of automatic unloading, material sorting and loading of coal coke storage cranes to improve the old crane system and realize intelligent and digital upgrades.

[0004] Therefore, in view of the above-mentioned technical problems and defects, it is urgent to design and develop a detection and processing method, system and platform suitable for the material surface of coal coke storage cranes. Summary of the invention

[0005] In order to overcome the above-mentioned deficiencies and difficulties in the prior art, the purpose of the present invention is to provide a method, system and platform for detecting and processing the material surface of a coal coke storage crane, so as to realize unmanned operation of the coal coke storage crane.

[0006] The first purpose of the present invention is to provide a detection and processing method suitable for the material surface of a coal coke storage crane; the second purpose of the present invention is to provide a detection and processing system suitable for the material surface of a coal coke storage crane; the third purpose of the present invention is to provide a detection and processing platform suitable for the material surface of a coal coke storage crane.

[0007] The first object of the present invention is achieved in that the method comprises the following steps:

[0008] Generate and obtain first data corresponding to the material surface of the coal coke storage crane to be detected and processed in real time; wherein the first data is parameter data corresponding to the material surface of the coal coke storage crane, including coordinate data of the crane, offset data of the crane and preset parameter data corresponding to the material surface of the coal coke storage crane;

[0009] Based on the first data, second data corresponding to the first data is generated, and the second data is preprocessed in real time to generate corresponding third data; wherein the second data is three-dimensional point cloud data; and the third data is preprocessed parameter data;

[0010] According to the third data, a first model corresponding to the material surface of the coal and coke storage to be detected and processed is constructed, and based on the first model, corresponding fourth data is generated; wherein, the first model is a 3D model; and the fourth data is the detection data of the material surface of the coal and coke storage.

[0011] The second object of the present invention is achieved in this way: the system is applied to the detection and processing method applicable to the material surface of the coal coke storage vehicle, and the system includes:

[0012] A data generation and acquisition unit is used to generate and acquire in real time first data corresponding to the material surface of the coal coke storage vehicle to be detected and processed; wherein the first data is parameter data corresponding to the material surface of the coal coke storage vehicle, including coordinate data of the vehicle, offset data of the vehicle, and preset parameter data corresponding to the material surface of the coal coke storage vehicle;

[0013] A first data generating unit is used to generate second data corresponding to the first data based on the first data, and pre-process the second data in real time to generate corresponding third data; wherein the second data is three-dimensional point cloud data; and the third data is pre-processed parameter data;

[0014] The second data generating unit is used to construct a first model corresponding to the material surface of the coal and coke storage to be detected and processed according to the third data, and generate corresponding fourth data based on the first model; wherein the first model is a 3D model; and the fourth data is the detection data of the material surface of the coal and coke storage.

[0015] The third object of the present invention is achieved in this way: the platform includes a processor, a memory and a detection and processing platform control program applicable to the material surface of the coal coke warehouse crane; wherein, the detection and processing platform control program applicable to the material surface of the coal coke warehouse crane is executed in the processor, and the detection and processing platform control program applicable to the material surface of the coal coke warehouse crane is stored in the memory, and the detection and processing platform control program applicable to the material surface of the coal coke warehouse crane implements the detection and processing method applicable to the material surface of the coal coke warehouse crane.

[0016] The present invention generates and obtains first data corresponding to the material surface of the coal coke storage vehicle to be detected and processed in real time through a method; wherein the first data is parameter data corresponding to the material surface of the coal coke storage vehicle, including coordinate data of the vehicle, offset data of the vehicle and preset parameter data corresponding to the material surface of the coal coke storage vehicle;

[0017] Based on the first data, second data corresponding to the first data is generated, and the second data is preprocessed in real time to generate corresponding third data; wherein the second data is three-dimensional point cloud data; and the third data is preprocessed parameter data;

[0018] According to the third data, a first model corresponding to the material surface of the coal coke storage crane to be detected and processed is constructed, and based on the first model, corresponding fourth data is generated; wherein, the first model is a 3D model; the fourth data is the material surface detection data of the coal coke storage crane, as well as a system and platform corresponding to the method, to realize unmanned operation of the coal coke storage crane.

[0019] In other words, the scheme of the present invention effectively solves the problems of coal coke storage crane material surface detection, point cloud processing, storage area three-dimensional modeling construction and presentation, grabbing point positioning and grabbing safety analysis, storage area material volume calculation and material accumulation detection at the material mouth. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0021] Figure 1 It is a schematic diagram of the system structure of an embodiment of a method for detecting and processing material surface of a coke storage vehicle according to the present invention;

[0022] Figure 2 This is a schematic diagram of the installation position of a laser radar in an embodiment of a method for detecting and processing the material surface of a coke storage vehicle according to the present invention;

[0023] Figure 3 It is a schematic diagram of a laser radar scanning sector (front view) of an embodiment of a detection and processing method for a material surface of a coke storage vehicle according to the present invention;

[0024] Figure 4 It is a schematic diagram of a laser radar scanning sector (side view) of an embodiment of a detection and processing method for a material surface of a coke storage vehicle according to the present invention;

[0025] Figure 5 This is a schematic diagram of the grid layout of the coal coke storage grabbing system according to an embodiment of the present invention, which is applicable to a method for detecting and processing the material surface of a coal coke storage vehicle;

[0026] Figure 6 It is a schematic diagram of a cloud map (grayscale) of sampling points scanned in a storage area of ​​a detection and processing method for a material surface of a coal coke storage vehicle according to the present invention;

[0027] Figure 7 This is a schematic diagram of the grid division and slope of an embodiment of a detection and processing method for a coke storage driving surface of the present invention;

[0028] Figure 8 It is a schematic flow chart of the steps of a detection and processing method applicable to the material surface of a coal coke storage crane of the present invention;

[0029] Fig. 9 The present invention is a schematic diagram of the architecture of a detection and processing system suitable for the material surface of a coal coke storage crane.

[0030] Fig.10 The present invention is a schematic diagram of the structure of a detection and processing platform suitable for the material surface of a coal coke storage crane. DETAILED DESCRIPTION

[0031] In order to better understand the purpose, technical solutions and advantages of the present invention, the present invention is further described below in conjunction with the accompanying drawings and specific implementation methods. Those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification.

[0032] The present invention may also be implemented or applied through other different specific examples, and the details in this specification may also be modified and changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention.

[0033] It should be noted that if the embodiments of the present invention involve directional indications (such as up, down, left, right, front, back, etc.), the directional indications are only used to explain the relative position relationship, movement status, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0034] In addition, if there are descriptions involving "first", "second", etc. in the embodiments of the present invention, the descriptions of "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or suggesting their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. Secondly, the technical solutions between the various embodiments can be combined with each other, but they must be based on the ability of ordinary technicians in the field to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0035] Preferably, the detection and processing method for the material surface of the coal coke storage vehicle of the present invention is applied in one or more terminals or servers. The terminal is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to microprocessors, application specific integrated circuits (ASIC), field programmable gate arrays (FPGA), digital signal processors (DSP), embedded devices, etc.

[0036] The terminal can be a computing device such as a desktop computer, a notebook, a PDA, a cloud server, etc. The terminal can interact with the client through a keyboard, a mouse, a remote control, a touch pad, or a voice control device.

[0037] The present invention realizes a detection and processing method, system, platform and storage medium suitable for the material surface of a coal coke storage crane.

[0038] like Figure 8 1 and 2 , which is a flow chart of a method for detecting and processing material surface in a coal coke storage provided by an embodiment of the present invention.

[0039] In this embodiment, the detection and processing method applicable to the material surface of the coal coke storage crane can be applied to a terminal with a display function or a fixed terminal. The terminal is not limited to a personal computer, a smart phone, a tablet computer, a desktop computer or an all-in-one computer equipped with a camera, etc.

[0040] The detection and processing method for the material surface of the charcoal depot can also be applied to a hardware environment composed of a terminal and a server connected to the terminal through a network. The network includes but is not limited to: a wide area network, a metropolitan area network or a local area network. The detection and processing method for the material surface of the charcoal depot in the embodiment of the present invention can be executed by a server, or by a terminal, or by both a server and a terminal.

[0041] For example, for a terminal that needs to perform detection and processing of the material surface of a coal coke depot, the detection and processing function of the material surface of a coal coke depot provided by the method of the present invention can be directly integrated on the terminal, or a client for implementing the method of the present invention can be installed. For another example, the method provided by the present invention can also be run on a server or other device in the form of a software development kit (SDK), and an interface for the detection and processing function of the material surface of a coal coke depot is provided in the form of SDK. The terminal or other device can implement the detection and processing function of the material surface of a coal coke depot through the provided interface. The present invention is further described below in conjunction with the accompanying drawings.

[0042] The present invention will be further described in detail below in conjunction with the accompanying drawings. Figure 1-Figure 8 As shown, the present invention provides a method for detecting and processing the material surface of a coke storage vehicle, wherein the method comprises the following steps:

[0043] S01, generating and acquiring first data corresponding to the material surface of the coal coke storage crane to be detected and processed in real time; wherein the first data is parameter data corresponding to the material surface of the coal coke storage crane, including coordinate data of the crane, offset data of the crane and preset parameter data corresponding to the material surface of the coal coke storage crane;

[0044] S02. Based on the first data, generate second data corresponding to the first data, and pre-process the second data in real time to generate corresponding third data; wherein the second data is three-dimensional point cloud data; and the third data is pre-processed parameter data;

[0045] S03. According to the third data, construct a first model corresponding to the material surface of the coal coke storage vehicle to be detected and processed, and generate corresponding fourth data based on the first model; wherein the first model is a 3D model; and the fourth data is the detection data of the material surface of the coal coke storage vehicle.

[0046] The real-time generation and acquisition of first data corresponding to the driving material surface of the coal coke storage to be detected and processed also includes:

[0047] S011. Generate and obtain fifth data corresponding to the laser radar; wherein the laser radar is a two-dimensional laser radar scanner; the fifth data is raw data of the laser radar, including scanning angle resolution data and scanning angle range data;

[0048] S012. Based on the first data, generate first control data corresponding to the first data; the first control data is control instruction data for controlling the lifting and opening and closing actions of the traveling trolley, car, and grab bucket.

[0049] The method of generating second data corresponding to the first data based on the first data, and preprocessing the second data in real time to generate corresponding third data, further includes:

[0050] S021, generating and acquiring sixth data corresponding to the driving state of the coal and coke depot, and generating corresponding second control data based on the sixth data; wherein the sixth data is the driving state data of the coal and coke depot; and the second control data is the control instruction data for activating the laser radar to start scanning;

[0051] S022. According to the first data, synchronously sample the current frame data and the current position data of the vehicle at least two laser radars at equal intervals, and generate corresponding second data;

[0052] S023, sequentially perform coordinate conversion processing, position correction processing, filtering processing and encoding processing on the second data, and generate and transmit corresponding third data.

[0053] The method further comprises: constructing a first model corresponding to the driving material surface of the coal coke storage to be detected and processed according to the third data, and generating corresponding fourth data based on the first model.

[0054] S031. Based on the first model, sequentially process the three-dimensional point cloud data corresponding to each frame; wherein the sequential processing includes filtering processing, storage processing and uniform downsampling processing;

[0055] S032. Generate and visualize a data grid corresponding to the three-dimensional point cloud data, and process the data grid by hole filling.

[0056] The method further comprises: constructing a first model corresponding to the driving material surface of the coal coke storage to be detected and processed according to the third data, and generating corresponding fourth data based on the first model.

[0057] S033. Generating seventh data corresponding to the driving of the coal and coke storage according to the fourth data, wherein the seventh data is grabbing parameter data of the grab bucket, including grabbing point data of the grab bucket and grabbing safety factor data;

[0058] S034, based on the seventh data, generating third control data corresponding to the crane operation in the coal coke storage; wherein the third control data is control instruction data for supplying the crane dispatching system with safety control of the automatic operation of the crane operation;

[0059] S035. Based on the first model and in combination with the fourth data, generate eighth data corresponding to the materials in the warehouse area and ninth data corresponding to the material port; wherein the eighth data is the volume data of the materials in the warehouse area; and the ninth data is the stacking status data of the materials at the material port.

[0060] Specifically, in the implementation of the scheme of the present invention, in order to realize the unmanned operation of the coal coke warehouse crane, it is necessary to first solve the coal coke warehouse material surface detection, grab point positioning and grab safety problems, and at the same time build a 3D model of the warehouse area, calculate the material volume of the warehouse area, and dynamically present the three-dimensional material surface of the warehouse area. This application uses two two-dimensional laser radar scanners with high precision, high angular resolution and medium and long-range characteristics to overcome the disadvantage of low reflectivity (about 5%) of black anthracite.

[0061] That is to say, in view of the low reflectivity of laser scanning coal tar powder, the large span of the bridge (31.5 meters) and the narrow spacing inside the main beam (1.4 meters), this scheme proposes a method and system for coal tar storage crane material surface detection and three-dimensional modeling. A two-dimensional laser radar scanner is installed on each side of the walkway of the bridge-type crane beam of the coal tar storage. The edge computing module communicates with the two laser radars and the crane PLC to collect the original data of the laser radar and the position data of the large vehicle X, small vehicle Y, grab bucket lifting height Z and grab bucket opening D in the crane PLC in real time. When the driving truck is driving, the edge computing module samples the current frame data of the laser radar at equal intervals according to the X coordinate of the large vehicle, and calculates and generates a three-dimensional point cloud by projection calculation. After filtering and encoding, it is uploaded to the 3D modeling module. The 3D modeling module collects each frame of three-dimensional point cloud, filters, stores, uniformly downsamples, performs display grid processing and hole filling, and then presents it. After the grab grid processing and grab safety analysis, it outputs the grab bucket grab point and grab safety factor, calculates the material volume in the storage area, and detects the material accumulation at the material mouth. The grabbing point and safety factor output by the system described in the solution of the present invention are supplied to the driving dispatching system to safely control the automatic operation of the driving.

[0062] The coal coke storage driving material surface detection and three-dimensional modeling system described in the scheme of the present invention includes two laser radars, an edge computing module, a 3D modeling module, a driving PLC module, and wired and wireless networks. Figure 1 The two laser radars are two-dimensional laser radar scanners, which can be configured with a scanning angle resolution of up to 0.04° and a scanning angle range of -90 to 90°. When scanning an object with a reflectance of 90%, the measuring distance can reach 130 meters, 40 meters at 10%, and about 26 meters at 5%. Taking the reflectance of anthracite of 5% as an example, it meets the distance measurement requirements of a crane with a lifting height of 18 meters. Install the 1# laser radar at 3 / 4 of the wide walkway of the coal coke storage bridge crane, and install the 2# laser radar at 1 / 4 of the narrow walkway, see attached. Figure 3 When installing the laser radar, the scanning sector should be as vertically downward as possible, parallel to the crane beam, and the laser beam at a 0° angle on the sector should be vertically downward to increase the echo intensity and effective reception rate of the laser on the coal coke surface and reduce the software angle correction coefficient.

[0063] The crane PLC module controls the lifting and opening and closing of the crane trolley, car and grab bucket manually and automatically through the driving dispatch system; the crane grab bucket position (X, Y, Z) and opening D are detected through the trolley and car Graham lines, grab bucket lifting and opening and closing drum absolute encoders. Edge computing obtains the crane reference point position in real time by quickly reading the crane PLC.

[0064] The edge computing module is composed of hardware, operating system and scanning control software. The hardware includes a six-core ARM@Carmel@v8.2 processor, 16GB RAM and ROM, 4 Gigabit Ethernet ports and power supply. The software includes a Linux operating system and scanning control software. Among them, the 4 Gigabit Ethernet ports are used to connect to the network with two laser radars, the driving PLC module, 3D modeling and debugging terminals. The edge computing module communicates with the two laser radars and the driving PLC, collects the data of the two laser radars and the driving position coordinates in the driving PLC in real time, and when the driving vehicle is driving, the current frame data of the two laser radars and the current position of the vehicle are synchronously sampled at equal intervals according to the X coordinate of the vehicle, and the three-dimensional coordinate projection calculation is performed according to the configuration parameters, and after coordinate conversion, position correction, filtering and encoding, it is uploaded to the 3D modeling module in real time. At the same time, a parameter configuration interface is provided for the host computer configuration interface to set parameters to meet the needs of on-site debugging and different application scenarios.

[0065] The 3D modeling module is composed of a server, an operating system, and a 3D modeling application software. The 3D modeling module collects each frame of 3D point cloud, filters, stores, uniformly downsamples, performs display grid processing, and fills holes before presentation. After the grid processing and grab safety analysis, the grabbing bucket grabbing point and grabbing safety factor are output, the material volume in the storage area is calculated, and the material accumulation at the material port is detected. The grabbing point and grabbing safety factor are transmitted to the driving dispatching system to control the automatic operation of the driving operation.

[0066] In other words, the solution of the present invention adds an edge computing module, two laser radars, wired and wireless networks, large and small Gray busbars, grab bucket hoisting opening and closing drum absolute encoders, crane PLC and other equipment to the original crane of the coal coke depot, installs a server in the ground electrical room, and installs a display terminal in the central control room. Network communication between the on-board equipment and the ground equipment is achieved through wired and wireless networks. The method and system for coal coke depot crane material surface detection and three-dimensional modeling described in the solution of the present invention have the following features and functions:

[0067] The system includes two laser radars, edge computing module, 3D modeling module, driving PLC module, wired and wireless network, see attached Figure 1 .

[0068] The coordinate system calibration of this system: from the perspective of the driver in the cab, the X-axis corresponds to the left driving direction of the truck, the Y-axis corresponds to the forward driving direction of the trolley, the Z-axis corresponds to the downward direction of the grab bucket, and D corresponds to the percentage of the grab bucket opening. The origin of the X-axis coordinate is at the right limit position of the truck, the origin of the Y-axis coordinate is at the position of the storage area wall on the rear limit side of the trolley, and the origin of the Z-axis coordinate is the midpoint position of the laser transmitter of the laser radar installed at a higher position (i.e., the reference laser radar). The midpoint of the bucket mouth when the grab bucket is closed and at the upper limit position needs to be corrected by the deviation height. The coordinates of the driving reference point (X, Y) are calibrated to the midpoint (X, Y) coordinates of the bucket mouth when the grab bucket is closed, and the Z coordinates of the driving reference point are calibrated to the Z coordinates of the reference laser radar. The accuracy of X, Y, and Z is in millimeter level, with a value range of X: 0 to 250,000 mm, Y: 0 to 35,000 mm, Z: 0 to 25,000 mm, and the value range of D is 0% to 110%.

[0069] The two laser radars are two-dimensional laser radar scanners, which can set the scanning angle resolution up to 0.04° and the scanning angle range from -90° to 90°; the scanning range is 130 meters when the diffuse reflectance is 90%, 40 meters when it is 10%, and about 26 meters when it is 5%. Taking the diffuse reflectance of anthracite of 5% as an example, it meets the ranging requirements of the 18-meter lifting height of the coal coke warehouse crane.

[0070] Two laser radars are installed on the sides of the platform on both sides of the vehicle. The 1# laser radar is installed at about 3 / 4 of the length of the wide platform, and the 2# laser radar is installed at about 1 / 4 of the length of the narrow platform. See the attached Figure 2 When installing the laser radar, try to make its scanning sector vertically downward, parallel to the crane beam, and the sector 0° angle laser beam vertically downward to increase the laser echo intensity and reception rate on the coal coke surface and reduce the scanning angle deviation.

[0071] The design of the laser radar bracket requires that the rotation angle of the laser radar on the XYZ axis can be fine-tuned to achieve mechanical correction of the scanning angle. Figure 2 During installation, the laser radar should avoid being blocked by surrounding equipment. Within the protection range of the vehicle buffer, the 1# laser radar should avoid being blocked by the driver's cab and stairs, and the 2# laser radar should avoid being blocked and rubbed by the tow cable.

[0072] The two laser radars are installed diagonally on the walkways on both sides of the vehicle to avoid mutual interference between laser beams and echoes, which will affect the measurement accuracy. In addition, the larger the laser oblique angle, the lower the echo intensity and the amount of reception, and the larger the distance between adjacent measurement points on the material surface. Therefore, the 1# laser radar focuses on scanning the right side of the storage area, and the 2# laser radar focuses on scanning the left side of the storage area. However, in order to avoid point cloud holes caused by the slope of the material surface, it is still necessary to retain full coverage of both sides of the storage area by the scanning sectors of the two laser radars. When the grab is open, the 1# laser radar is far away from the grab, and the 2# laser radar barely avoids the obstruction of the grab, but it may be obstructed when the grab swings. Therefore, when scanning the storage area, follow the principle of grab closure. When the truck is moving materials normally, the grab obstruction area is filtered out according to the opening and closing status of the grab. See attached Figures 2 to 4 .

[0073] The parameters involved in the installation and point cloud fusion of the two laser radars are: the height of the reference laser radar to the ground, the X-axis offset, Y-axis offset, and Z-axis offset of the 1# and 2# laser radars and the driving reference point, and the Y-axis rotation offset, X-axis rotation offset, and Z-axis rotation offset of the scanning angle of the 1# and 2# laser radars.

[0074] The crane PLC module controls the lifting and opening and closing of the crane trolley, car and grab bucket manually and automatically through the driving dispatch system in the driver's cab; the crane grab bucket position (X, Y, Z) and grab bucket opening D are detected in real time through the trolley and car Graham lines, grab bucket lifting and opening and closing drum absolute encoders. X represents the trolley coordinates, Y represents the trolley coordinates, Z represents the lifting height, and D represents the grab bucket opening. Edge computing obtains the driving reference point position by quickly reading the crane PLC.

[0075] The edge computing module is composed of hardware, operating system and scanning control software. The hardware includes a six-core ARM@Carmel@v8.2 processor, 16GB RAM and ROM, 4 Gigabit Ethernet ports and a power supply. The software includes a Linux operating system and scanning control software. The 4 Gigabit Ethernet ports are used to connect to the two laser radars, the driving PLC, the 3D modeling and debugging terminals. The edge computing module communicates with the two laser radars and the driving PLC TCP, collects the data of the two laser radars and the driving position coordinates in the driving PLC in real time, and synchronously samples the current frame data of the two laser radars and the current position coordinates of the driving according to the X coordinate of the vehicle when the driving vehicle is driving. According to the configuration parameters, three-dimensional coordinate projection calculation, coordinate conversion, position correction, filtering and encoding are performed, and the encoded message is sent to the 3D modeling module according to the queue. The edge computing provides a parameter configuration interface for the host computer configuration interface to set parameters to meet the needs of on-site debugging and applications in different scenarios.

[0076] The edge computing scanning control software is divided into three submodules: network communication, scanning control, and 3D point cloud computing. The network communication submodule realizes communication with 1# laser radar, 2# laser radar, driving PLC, 3D modeling, and parameter configuration interface. Create a TCP client connected to the two laser radars and driving PLC, a TCP server connected to the parameter configuration interface, and a UDP sender for 3D modeling communication, and send heartbeat packets to the 3D modeling module regularly. The edge computing automatically runs the scanning control software when it is powered on, initializes the IP address and port number configuration parameters of 1#, 2# laser radar, edge computing, driving PLC, and 3D modeling, and generates a TCP Modbus station number. Monitor the communication connection status with the two laser radars and driving PLC, and reconnect the network if the communication is interrupted. Refresh the status of the heartbeat packet sent to 3D modeling in real time according to the network status: 0-default invalid, 1-system normal, 2-edge computing abnormal, 3-1# laser radar communication abnormal, 4-2# laser radar communication abnormal, 5-driving PLC communication abnormal.

[0077] The scanning control submodule implements the following functions: when powered on or disconnected from the network and reconnected, the system parameters and status of the two laser radars are read out for analysis, and the laser radar status, scanning frequency, scanning angle resolution, starting angle, ending angle and data length are obtained for subsequent projection calculations. After the laser radar initialization is completed, the laser radar is enabled to continuously scan and upload data; the current data of the laser radar is received and stored, and the line position coordinates are read regularly according to the PLC cycle parameters. At the same time, the X coordinate change dx of the driving vehicle is monitored, and the current frame data of the laser radar and the current driving position coordinate data are synchronously packaged and stored or discarded; the queue entry, sorting and dequeue mechanism of the control frame point cloud message sending queue is controlled.

[0078] The three-dimensional point cloud computing submodule realizes the following functions: when the X-coordinate change dx of the large vehicle is monitored ≥ the X-distance sampling threshold of the large vehicle, the Y-axis rotation offset, X-axis rotation offset and Z-axis rotation offset parameters of the scanning angles of 1# and 2# laser radars are added to correct them, and the upper and lower thresholds of the scanning angle filters of 1# and 2# laser radars are directly filtered. The three-dimensional point cloud of the current data frame of the two laser radars is projected and calculated. Combined with the current driving coordinates and the X-axis offset, Y-axis offset and Z-axis offset parameters of the 1# and 2# laser radars and the driving reference point, the three-dimensional coordinates based on the coordinate systems of the two laser radars are converted to the coordinate system based on this system, and then combined with the upper and lower threshold parameters of the X-axis filter of the point cloud, the upper and lower threshold parameters of the Y-axis filter of 1# and 2# laser radars, and the upper and lower threshold parameters of the Z-axis filter, the blocked area is filtered out according to the grab opening, and then the coordinates of the two frames of point cloud are encoded and loaded into the sending queue, and the queue is quickly sent to the 3D modeling module.

[0079] The edge computing readable and writable parameters include reading the PLC coordinate cycle, the X-distance sampling threshold of the large vehicle, the reference laser radar to the ground height, the upper and lower thresholds of the X-axis filter of the point cloud, the upper and lower thresholds of the Y-axis filter of the 1# and 2# laser radars, the upper and lower thresholds of the Z-axis filter, the X-axis offset, Y-axis offset, and Z-axis offset of the 1# and 2# laser radars and the driving reference point, the Y-axis rotation offset, X-axis rotation offset, and Z-axis rotation offset of the scanning angle of the 1# and 2# laser radars, and the upper and lower thresholds of the scanning angle filter of the 1# and 2# laser radars. Read-only parameters include the edge computing device status, the 1# and 2# laser radar status, the communication status with the 1# and 2# laser radars, the communication status with the driving PLC, the heartbeat status for 3D modeling, and the scanning frequency, angle resolution, scanning start angle, and scanning end angle of the 1# and 2# laser radars. The configurable IP address and port number parameters include 1# and 2# LiDAR IP addresses and port numbers, the IP address and port number of the vehicle PLC, the IP address and port number of 3D modeling, the local IP address and service port number of edge computing, and the edge computing device restart interface parameters. When the vehicle is manually stopped, the edge computing module can be restarted remotely through the network.

[0080] The 3D modeling module is composed of a server, a display terminal, an operating system and a 3D modeling application software. The 3D modeling module collects each frame of 3D point cloud, stores, filters, uniformly samples, performs display grid processing and hole filling, and then presents it. After the grid processing and grab safety analysis, the grabbing point and grab safety factor of the grab bucket are output, the material volume of the storage area is calculated, and the material accumulation at the material port is detected. The grabbing point and grab safety factor are transmitted to the driving dispatching system to control the automatic operation of the driving.

[0081] The 3D modeling module collects 3D point cloud data and stores it in the original point cloud area of ​​the RAM area. The accumulated received frame point cloud X coordinates are limited to the upper and lower limit thresholds of the X coordinates (i.e. within the 3 storage areas). When the refresh cycle arrives, outlier filtering, Y and Z pass-through filtering, uniform downsampling, and hole filling (method 1) are uniformly performed. When scanning and updating regional data, each time a new data frame is received, it is necessary to compare it with the data frame adjacent to the X coordinate in the original point cloud area, replace the data frame with the smallest adjacent distance on both sides of X, and uniformly filter and uniformly sample it when the refresh cycle arrives, and then transfer it to the sampling point cloud area. See the attached Figure 6 Hole filling method 1: Find holes and use the center point of the hole as the seed point, grow the region from the seed point to the hole edge point as the radius R, and then grow outward to 2R, analyze the 2R->R trend and perform linear filling, and store the filled point cloud in the sampling point cloud area. This method is more complicated and can be replaced by method 2 described below.

[0082] Display grid processing: With a certain (X,Y) grid size, for example {(X,Y) = (10,10) cm}, the sampling point cloud area is divided into many (X,Y) display grids, the Z average value of the points in each (X,Y) display grid is calculated as Zavg, and the new grid coordinate point (Xmid,Ymid,Zavg) is formed with the midpoint (Xmid,Ymid) of the (X,Y) display grid. If there are holes in the grid, the holes are filled (explained below). In this way, the disordered point cloud in the sampling point cloud area is converted into an ordered point cloud, which can then be converted into a two-dimensional array or image format for storage, and then this two-dimensional array or image is imported into the WPF framework model (such as Regular Grid Data) and presented to the display terminal in the central control room, and refreshed according to a certain display cycle, such as once every 10 seconds.

[0083] Hole filling (method 2): During the display gridding process, there may be no coordinate points in the divided display grid. The grid is considered empty, called a hole or a hole grid, and the coordinates are marked as (Xmid, Ymid, -1). Hole filling is required during processing: take the hole grid as the midpoint, take the Z average value of the neighboring grids within a certain neighborhood radius R (for example, R = 3) and record it as Zrep, and replace the hole grid coordinates with (Xmid, Ymid, Zrep).

[0084] Grab grid processing: define (X,Y) grab grid according to grab bucket size, for example {(X,Y)=(3.9,1.8) meters}, based on display grid data, divide the grab points into many (X,Y) grab grids according to the experience of the storage area, calculate the average value of each (X,Y) grab grid point Z as Zavg, and form a new grid coordinate (Xmid,Ymid,Zavg) with the midpoint (Xmid,Ymid) of the (X,Y) grab grid. See the attached figure for the grab grid layout adapted to the coal coke storage after actual testing. Figure 5 There should be a certain intersection between the grabbing grids in the length and width directions, especially the intersection area in the opening and closing direction of the grab bucket should be larger, so that the material surface flatness will be better after sequential grabbing.

[0085] Configuration of grabbing grid point model in coal coke storage: The grabbing grid layout can be designed according to the actual scenario, set through the configuration interface of the storage area 3D model, and stored in the database of the 3D modeling module. It can be added, deleted, modified, and searched as needed. The driving dispatching system can read the grabbing grid midpoint (X, Y) coordinates from the database and read the corresponding grabbing point coordinates (X, Y, Z) from the grabbing grid storage area of ​​the 3D modeling module. The discharge point coordinates of the three material ports are configured as fixed positions directly above the material ports and stored in the database. The side of the grabbing grid in the storage area close to the material port is the coal storage area, and the side close to the coal unloading lane is the coal unloading area.

[0086] Retaining wall, fence and material opening model configuration: From the perspective of the driving driver, the four retaining walls are described by the front centerline point (X1, Y1, Z1) and the rear centerline point (X2, Y2, Z2) and the thickness W and height H of the retaining wall. When processing, they are converted into a rectangular cube protection range with the starting point (X1-W / 2, Y1, H) and the end point (X2+W / 2, Y2, H). The fence model configuration method is the same as the retaining wall. Due to the front and rear limit protection restrictions of the driving trolley, the grab bucket cannot collide with the fence (horizontally), and it can also be not configured. The material opening model configuration is configured into the database with the four corner points of the bottom outer edge of the material opening fence and the material opening height. When processing, a cube protection range with the lower left corner point as the starting point and the upper right corner point as the end point is formed. The retaining wall, fence and material opening models are mainly used to prevent the driving (X, Y, Z) coordinates from entering the protection range, prevent the grab bucket from hitting the wall, and avoid safety accidents. In addition, based on the retaining wall, fence and material opening models, the retaining wall, fence and material opening areas can be solidified on the three-dimensional warehouse area display interface, and the point cloud data of the area will no longer be updated, making the three-dimensional warehouse area display more beautiful.

[0087] Safety analysis of grabbing points: Based on the grabbing grid and display grid data, divide the (X,Y) grabbing grid into 6 small grids, calculate the Z average value of the display grid points in each of the 6 small grids and record it as Za1~Za6, and then analyze the slope problem of the grabbing grid material surface according to the relative position of the 6 small grids and the values ​​of Za1~Za6. Find the maximum and minimum values ​​in Za1~Za6 and record them as Zmax and Zmin. First, use the condition (Zmax-Zmin≤grab safety slope threshold, for example, set the threshold as the height of the grab jaw) to prioritize the safe grabbing points; if this condition is not met, then perform slope position analysis. Attachment Figure 7 (a) is the division of the grabbing grid, and the rest lists several typical grabbing grid slope positions, (b) is the outer slope, (c) is the inner slope, (d) is the right slope, (e) is the left slope, (f) is the foot of the right slope, (g) is the head of the right slope, (h) is the middle concave, and (i) is the middle convex. (j~l) and others have no obvious rules, but like (h~i), they can be considered not on the slope, and the grabbing safety is higher than (b~g), and the grabbing safety of (f~g) is higher than (b~e). The "high", "medium" and "low" labels in the figure are divided by three height segments calculated by (Zmax-Zmin) / 3. In the above-mentioned situations, as long as the height difference (Zmax-Zmin) is controlled within a certain threshold, the grabbing safety can be guaranteed. However, the judgment threshold corresponding to being on a slope is much more stringent, and the selection of these thresholds needs to be determined through on-site measurements, based on the fact that the grab is not tilted too much, the grab pulley block does not get unglued, and the swing of the grab is within an acceptable range when it is lifted.

[0088] Calculation of the material volume in the warehouse area: Based on the display grid data, assuming that the XY area of ​​each display grid is Sn and the height is Zn, the volume of the display grid is Sn*Zn, and the formula for the material volume in the warehouse area can be deduced as follows:

[0089]

[0090] Material accumulation detection at the material mouth: Based on the display grid data, the depth data of the display grid of the material mouth area is extracted according to the starting point and end point of the material mouth model and converted into a depth image format, and then the depth image is converted into a grayscale image, and the actual material mouth height is proportionally converted into the material mouth grayscale threshold of the grayscale image, and the deviation threshold is added as the material mouth accumulation judgment threshold; traversal judgment (grayscale image pixel value - material mouth accumulation judgment threshold>0) and statistics of multiple groups of continuous pixel points that meet this condition are recorded as Ni (i=0~m), and the maximum value of (grayscale image pixel value - material mouth accumulation judgment threshold) is recorded as Hmax. If Ni=0, there is no material accumulation at the material mouth. If Ni>0 and Hmax>the maximum material accumulation judgment threshold, there is material accumulation at the material mouth. The larger Ni and Hmax are, the larger the material pile is, and the larger i is, the more material piles there are.

[0091] The method described in the scheme of the present invention requires that automatic material grabbing must follow the large vehicle's frequent driving and timely refresh of the material surface area that has been grabbed to avoid deviations in the height of the grabbing point due to untimely scanning, and avoid deviations by automatically operating the warehouse area for the first time and regularly starting the scanning disk warehouse to refresh data.

[0092] To achieve the above object, the present invention also provides a detection and processing system suitable for the material surface of the coal coke storage vehicle, such as Fig. 9 As shown, the system is applied to the detection and processing method applicable to the material surface of the coal coke storage vehicle, and the system includes:

[0093] A data generation and acquisition unit is used to generate and acquire in real time first data corresponding to the material surface of the coal coke storage vehicle to be detected and processed; wherein the first data is parameter data corresponding to the material surface of the coal coke storage vehicle, including coordinate data of the vehicle, offset data of the vehicle, and preset parameter data corresponding to the material surface of the coal coke storage vehicle;

[0094] A first data generating unit is used to generate second data corresponding to the first data based on the first data, and pre-process the second data in real time to generate corresponding third data; wherein the second data is three-dimensional point cloud data; and the third data is pre-processed parameter data;

[0095] The second data generating unit is used to construct a first model corresponding to the material surface of the coal and coke storage to be detected and processed according to the third data, and generate corresponding fourth data based on the first model; wherein the first model is a 3D model; and the fourth data is the detection data of the material surface of the coal and coke storage.

[0096] The data generation and acquisition unit further includes:

[0097] A first generating module is used to generate and obtain fifth data corresponding to the laser radar; wherein the laser radar is a two-dimensional laser radar scanner; the fifth data is raw data of the laser radar, including scanning angle resolution data and scanning angle range data;

[0098] A second generating module is used to generate first control data corresponding to the first data based on the first data; the first control data is control instruction data for controlling the lifting and opening and closing actions of the traveling trolley, the trolley, and the grab bucket;

[0099] And / or, the first data generating unit further includes:

[0100] The third generating module is used to generate and obtain sixth data corresponding to the driving state of the coal and coke depot, and generate corresponding second control data based on the sixth data; wherein the sixth data is the driving state data of the coal and coke depot; and the second control data is the control instruction data for activating the laser radar to start scanning;

[0101] A fourth generating module, configured to synchronously sample current frame data of at least two laser radars and current position data of the vehicle at equal intervals according to the first data, and generate corresponding second data;

[0102] A first processing module, used for sequentially performing coordinate conversion processing, position correction processing, filtering processing and encoding processing on the second data, and generating and transmitting corresponding third data;

[0103] And / or, the second data generating unit further includes:

[0104] A second processing module, used to sequentially process the three-dimensional point cloud data corresponding to each frame based on the first model; wherein the sequential processing includes filtering processing, storage processing and uniform downsampling processing;

[0105] The third processing module is used to generate and visually display a data grid corresponding to the three-dimensional point cloud data, and perform hole filling processing on the data grid.

[0106] The second data generating unit further includes:

[0107] A fifth generating module, used to generate seventh data corresponding to the driving of the coal coke storage according to the fourth data, wherein the seventh data is grabbing parameter data of the grab bucket, including grabbing point data of the grab bucket and grabbing safety factor data;

[0108] A sixth generating module is used to generate third control data corresponding to the crane driving in the coal coke storage based on the seventh data; wherein the third control data is control instruction data for supplying the crane dispatching system with safety control of the automatic operation of the crane driving;

[0109] The seventh generation module is used to generate, based on the first model and in combination with the fourth data, the eighth data corresponding to the materials in the warehouse area and the ninth data corresponding to the material port; wherein the eighth data is the volume data of the materials in the warehouse area; and the ninth data is the stacking status data of the materials at the material port.

[0110] In the system solution embodiment of the present invention, the method steps involved in the detection and processing of the material surface of the coal coke storage crane have been described above in detail. That is to say, the functional modules in the system are used to implement the steps or sub-steps in the above method embodiment, which will not be repeated here.

[0111] To achieve the above object, the present invention also provides a detection and processing platform suitable for the material surface of the coal coke storage vehicle, such as Fig.10 As shown, it includes a processor, a memory, and a detection and processing platform control program applicable to the material surface of the coal coke depot; wherein, the detection and processing platform control program applicable to the material surface of the coal coke depot is executed by the processor, the detection and processing platform control program applicable to the material surface of the coal coke depot is stored in the memory, and the detection and processing platform control program applicable to the material surface of the coal coke depot implements the detection and processing method steps applicable to the material surface of the coal coke depot. For example:

[0112] S01, generating and acquiring first data corresponding to the material surface of the coal coke storage crane to be detected and processed in real time; wherein the first data is parameter data corresponding to the material surface of the coal coke storage crane, including coordinate data of the crane, offset data of the crane and preset parameter data corresponding to the material surface of the coal coke storage crane;

[0113] S02. Based on the first data, generate second data corresponding to the first data, and pre-process the second data in real time to generate corresponding third data; wherein the second data is three-dimensional point cloud data; and the third data is pre-processed parameter data;

[0114] S03. According to the third data, construct a first model corresponding to the material surface of the coal coke storage vehicle to be detected and processed, and generate corresponding fourth data based on the first model; wherein the first model is a 3D model; and the fourth data is the detection data of the material surface of the coal coke storage vehicle.

[0115] The specific details of the steps have been explained above and will not be repeated here.

[0116] In the embodiment of the present invention, the built-in processor of the detection and processing platform applicable to the material surface of the coal coke depot can be composed of an integrated circuit, for example, it can be composed of a single packaged integrated circuit, or it can be composed of a plurality of integrated circuits with the same or different functions, including one or more central processing units (CPU), microprocessors, digital processing chips, graphics processors and various control chips. The processor uses various interfaces and lines to connect various components, and executes or executes programs or units stored in the memory, and calls data stored in the memory to perform various functions and process data applicable to the detection and processing of the material surface of the coal coke depot;

[0117] The memory is used to store program codes and various data. It is installed in the detection and processing platform suitable for the material surface of the coal coke storage crane, and realizes high-speed and automatic access to programs or data during operation.

[0118] The memory includes read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electronically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, magnetic disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0119] The present invention generates and obtains the first data corresponding to the material surface of the coal coke storage driving to be detected and processed in real time through a method; wherein the first data is parameter data corresponding to the material surface of the coal coke storage driving, including the coordinate data of the driving, the offset data of the driving and the preset parameter data corresponding to the material surface of the coal coke storage driving; based on the first data, generates the second data corresponding to the first data, and pre-processes the second data in real time to generate the corresponding third data; wherein the second data is three-dimensional point cloud data; the third data is the pre-processed parameter data; according to the third data, constructs a first model corresponding to the material surface of the coal coke storage driving to be detected and processed, and generates the corresponding fourth data based on the first model; wherein the first model is a 3D model; the fourth data is the material surface detection data of the coal coke storage driving, and the system and platform corresponding to the method realize the unmanned operation of the coal coke storage driving. That is to say, through the scheme of the present invention, the problems of material surface detection, point cloud processing, three-dimensional modeling construction and presentation of the storage area, grasping point positioning and grasping safety analysis, storage area material volume calculation and material accumulation detection at the material port are effectively solved.

[0120] The above-mentioned embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

Claims

1. A method for detecting and processing the material surface of a coal coke storage vehicle, characterized in that: The method comprises the steps of: Generate and obtain first data corresponding to the material surface of the coal coke storage crane to be detected and processed in real time; wherein the first data is parameter data corresponding to the material surface of the coal coke storage crane, including coordinate data of the crane, offset data of the crane and preset parameter data corresponding to the material surface of the coal coke storage crane; Based on the first data, second data corresponding to the first data is generated, and the second data is preprocessed in real time to generate corresponding third data; wherein the second data is three-dimensional point cloud data; and the third data is preprocessed parameter data; According to the third data, a first model corresponding to the material surface of the coal and coke storage to be detected and processed is constructed, and based on the first model, corresponding fourth data is generated; wherein, the first model is a 3D model; and the fourth data is the detection data of the material surface of the coal and coke storage.

2. A method for detecting and processing the material surface of a coal coke storage vehicle according to claim 1, characterized in that: The real-time generation and acquisition of first data corresponding to the driving material surface of the coal coke storage to be detected and processed also includes: Generate and obtain fifth data corresponding to the laser radar; wherein the laser radar is a two-dimensional laser radar scanner; the fifth data is the laser radar raw data, including scanning angle resolution data and scanning angle range data; Based on the first data, first control data corresponding to the first data is generated; the first control data is control instruction data for controlling the lifting and opening and closing actions of the traveling trolley, trolley and grab bucket.

3. A method for detecting and processing the material surface of a coal coke storage vehicle according to claim 1, characterized in that: The method of generating second data corresponding to the first data based on the first data, and preprocessing the second data in real time to generate corresponding third data, further includes: Generate and obtain sixth data corresponding to the driving state of the coal and coke depot, and generate corresponding second control data based on the sixth data; wherein the sixth data is the driving state data of the coal and coke depot; and the second control data is the control instruction data for activating the laser radar to start scanning; According to the first data, synchronously sample the current frame data of at least two laser radars and the current position data of the vehicle at equal intervals, and generate corresponding second data; The second data is processed by coordinate conversion, position correction, filtering and encoding in sequence, and the corresponding third data is generated and transmitted.

4. A method for detecting and processing the material surface of a coal coke storage vehicle according to claim 1, characterized in that: The method further comprises: constructing a first model corresponding to the driving material surface of the coal coke storage to be detected and processed according to the third data, and generating corresponding fourth data based on the first model. Based on the first model, sequentially processing the three-dimensional point cloud data corresponding to each frame; wherein the sequential processing includes filtering processing, storage processing and uniform downsampling processing; A data grid corresponding to the three-dimensional point cloud data is generated and visually displayed, and the data grid is processed by hole filling.

5. A method for detecting and processing the material surface of a coal coke storage vehicle according to claim 1 or 4, characterized in that: The method further comprises: constructing a first model corresponding to the driving material surface of the coal coke storage to be detected and processed according to the third data, and generating corresponding fourth data based on the first model. According to the fourth data, seventh data corresponding to the driving of the coal coke storage is generated respectively, wherein the seventh data is grabbing parameter data of the grab bucket, including grabbing point data of the grab bucket and grabbing safety factor data; Based on the seventh data, third control data corresponding to the crane operation in the coal coke storage is generated; wherein the third control data is control instruction data for supplying the crane dispatching system with safety control of the automatic operation of the crane operation; Based on the first model and in combination with the fourth data, eighth data corresponding to the materials in the storage area and ninth data corresponding to the material port are generated respectively; wherein the eighth data is the volume data of the materials in the storage area; and the ninth data is the stacking status data of the materials at the material port.

6. A detection and processing system suitable for the material surface of a coal coke storage vehicle, characterized in that: The system is applied to the detection and processing method for the material surface of the coal coke storage vehicle as claimed in any one of claims 1 to 5, and the system comprises: A data generation and acquisition unit is used to generate and acquire in real time first data corresponding to the material surface of the coal coke storage vehicle to be detected and processed; wherein the first data is parameter data corresponding to the material surface of the coal coke storage vehicle, including coordinate data of the vehicle, offset data of the vehicle, and preset parameter data corresponding to the material surface of the coal coke storage vehicle; A first data generating unit is used to generate second data corresponding to the first data based on the first data, and pre-process the second data in real time to generate corresponding third data; wherein the second data is three-dimensional point cloud data; and the third data is pre-processed parameter data; The second data generating unit is used to construct a first model corresponding to the material surface of the coal and coke storage to be detected and processed according to the third data, and generate corresponding fourth data based on the first model; wherein the first model is a 3D model; and the fourth data is the detection data of the material surface of the coal and coke storage.

7. A detection and processing system for the material surface of a coal coke storage vehicle according to claim 6, characterized in that: The data generation and acquisition unit further includes: A first generating module is used to generate and obtain fifth data corresponding to the laser radar; wherein the laser radar is a two-dimensional laser radar scanner; the fifth data is raw data of the laser radar, including scanning angle resolution data and scanning angle range data; A second generating module is used to generate first control data corresponding to the first data based on the first data; the first control data is control instruction data for controlling the lifting and opening and closing actions of the traveling trolley, the trolley, and the grab bucket; And / or, the first data generating unit further includes: The third generating module is used to generate and obtain sixth data corresponding to the driving state of the coal and coke depot, and generate corresponding second control data based on the sixth data; wherein the sixth data is the driving state data of the coal and coke depot; and the second control data is the control instruction data for activating the laser radar to start scanning; A fourth generating module, configured to synchronously sample current frame data of at least two laser radars and current position data of the vehicle at equal intervals according to the first data, and generate corresponding second data; A first processing module, used for sequentially performing coordinate conversion processing, position correction processing, filtering processing and encoding processing on the second data, and generating and transmitting corresponding third data; And / or, the second data generating unit further includes: A second processing module, used to sequentially process the three-dimensional point cloud data corresponding to each frame based on the first model; wherein the sequential processing includes filtering processing, storage processing and uniform downsampling processing; The third processing module is used to generate and visually display a data grid corresponding to the three-dimensional point cloud data, and perform hole filling processing on the data grid.

8. A detection and processing system for the material surface of a coal coke storage vehicle according to claim 6 or 7, characterized in that: The second data generating unit further includes: A fifth generating module, used to generate seventh data corresponding to the driving of the coal coke storage according to the fourth data, wherein the seventh data is grabbing parameter data of the grab bucket, including grabbing point data of the grab bucket and grabbing safety factor data; A sixth generating module is used to generate third control data corresponding to the crane driving in the coal coke storage based on the seventh data; wherein the third control data is control instruction data for supplying the crane dispatching system with safety control of the automatic operation of the crane driving; The seventh generation module is used to generate, based on the first model and in combination with the fourth data, the eighth data corresponding to the materials in the warehouse area and the ninth data corresponding to the material port; wherein the eighth data is the volume data of the materials in the warehouse area; and the ninth data is the stacking status data of the materials at the material port.

9. A detection and processing platform suitable for the material surface of a coal coke storage crane, characterized in that: It includes a processor, a memory and a detection and processing platform control program applicable to the material surface of a coal coke depot. The detection and processing platform control program applicable to the material surface of a coal coke depot is executed by the processor, and the detection and processing platform control program applicable to the material surface of a coal coke depot is stored in the memory. The detection and processing platform control program applicable to the material surface of a coal coke depot implements the detection and processing method applicable to the material surface of a coal coke depot as described in any one of claims 1 to 5.

Images