Transportation material weighing system and weighing method based on laser radar

Abstract

The invention discloses a transported material weighing system and weighing method based on a laser radar, relates to the technical field of material transportation, and solves the problems that the net volume of materials is not accurate enough and the material volume is not accurate due to the fact that the calculated material volume is the material volume containing the contained materials because the material volume of a car hopper is not considered in the prior art. And the accuracy is low when the material weight is calculated. After material point cloud data is generated according to the parameter data and the transportation point cloud data, the material volume is calculated; generating material weight according to the material volume and the comprehensive density; a material falling coefficient is generated according to the material point cloud data, an early warning signal is generated according to the material falling coefficient, the material volume of a container where materials are discharged during calculation of the material volume, different densities of materials of different types and different sizes in a transport vehicle hopper are considered, and the comprehensive density is used for replacing the material density and the net volume to calculate the more accurate material weight. And the accuracy of calculating the material weight during material transportation is improved.

Description

Technical Field

[0001] The present application belongs to the field of material transportation technology, and specifically is a laser radar-based transportation material weighing system and weighing method. Background Art

[0002] Material transportation refers to the process of moving raw materials, parts, finished products and other physical materials from one geographical location to another by means of specific transportation tools. Common modes of material transportation include road transportation, rail transportation, water transportation and air transportation. In the process of material transportation, the accuracy and stability of the weighing system are crucial to ensure transportation safety and efficiency. Traditional weighing methods often rely on static weighing or manual visual inspection, which are not only time-consuming and labor-intensive, but also have certain errors. With the development of technology, lidar, as a high-precision and high-efficiency sensing device, has gradually been applied to the field of material transportation.

[0003] The prior art (invention patent application with publication number CN116086577A) discloses an excavator weighing system based on laser radar and camera device, including hardware part and software part. The hardware part includes an industrial computer, a bucket width recognition device, a bucket side profile recognition device and a material surface recognition device. The software part includes a recognition and segmentation module and an analysis and calculation module. The recognition and segmentation module includes a feature position judgment module and a segmentation extraction module. The analysis and calculation module includes a bucket width analysis module, a bucket side profile analysis module and a material surface analysis module.

[0004] The above scheme calculates the volume of the material in the bucket by scanning the width and side profile data of the bucket through the laser radar, and calculates the volume of the material exceeding the bucket according to the material surface recognition device. The two are added together to obtain the total volume of the material, and then the weight of the material in the bucket is calculated according to the material density. The volume of the material in the bucket is calculated by using the width and side profile data of the bucket, but the material volume of the bucket itself is not considered, so that the calculated material volume includes the material volume of the material, resulting in the net volume of the material being inaccurate, which in turn leads to low accuracy in calculating the material weight. Therefore, the laser radar transport material weighing system still needs to be further improved. Summary of the invention

[0005] The present application aims to solve at least one of the technical problems existing in the prior art; to this end, the present application proposes a transport material weighing system and a weighing method based on laser radar, which are used to solve the technical problem that the prior art fails to consider the material volume of the truck bed itself when calculating the material volume through laser radar scanning, so that the calculated material volume includes the material volume of the material contained, resulting in the net volume of the material being inaccurate, which in turn leads to low accuracy in calculating the material weight.

[0006] To achieve the above-mentioned purpose, the first aspect of the present application provides a transport material weighing system based on laser radar, including: a data acquisition module, a data processing module, a data analysis module, an early warning module and a database;

[0007] The data acquisition module is used to acquire transportation data through a data acquisition device; the transportation data includes a transportation vehicle ID and transportation point cloud data;

[0008] The data processing module is used to preprocess the transport point cloud data to obtain preprocessed transport point cloud data;

[0009] The data analysis module: obtains the parameter data of the transport vehicle and the material data and comprehensive density of the transported material in the transport query table according to the transport vehicle ID; generates material point cloud data according to the parameter data and the transport point cloud data, and then calculates the material volume; generates the material weight according to the material volume and comprehensive density; generates the material shedding coefficient according to the material point cloud data; generates an early warning signal according to the material shedding coefficient and the material weight;

[0010] The early warning module: makes corresponding prompts according to the early warning signals and contacts the management personnel.

[0011] The present application obtains the parameter data of the transport vehicle and the material data and comprehensive density of the transported materials in the transport query table according to the transport vehicle ID; generates material point cloud data according to the parameter data and the transport point cloud data, and then calculates the material volume; generates material weight according to the material volume and comprehensive density; generates material shedding coefficient according to the material point cloud data; generates an early warning signal according to the material shedding coefficient and the material weight, and excludes the material volume of the container where the material is located when calculating the material volume, and considers that the densities of materials of different types and sizes in the transport bucket are different, and uses the comprehensive density instead of the material density and the net volume to calculate a more accurate material weight, thereby improving the accuracy of calculating the material weight when transporting materials.

[0012] Furthermore, the data preprocessing includes a denoising operation and a downsampling operation.

[0013] Furthermore, the construction of the transport query table includes the following steps:

[0014] Obtain several transport vehicle IDs and their corresponding parameter data, material data and their corresponding comprehensive density; the comprehensive density changes with the type and size of the material loaded on the transport vehicle each time

[0015] A transport query table is created with several transport vehicle IDs and their corresponding parameter data, material data and their corresponding comprehensive density.

[0016] Furthermore, the comprehensive density is generated through material data, including:

[0017] Get material types and material size ranges from some historical material data;

[0018] Put materials of several material size ranges of material types into various containers, and obtain the net weight JZi and net volume Vi of the materials in various containers;

[0019] The comprehensive density ZMi corresponding to several different material sizes in the material category is calculated by the formula ZMi=JZi / Vi; wherein i represents the material number of several different material sizes in each material category, i=1, 2, …, M; M is the total number of different material sizes in the material category;

[0020] The comprehensive density of each material size range in several material types is composed into a comprehensive density table.

[0021] Furthermore, the step of calculating the material volume after generating the material point cloud data according to the parameter data and the transportation point cloud data includes:

[0022] Obtain parameter data and transportation point cloud data;

[0023] Generate material point cloud data based on parameter data and transportation point cloud data;

[0024] Construct a triangular mesh model based on the material point cloud data, and divide the triangular mesh model into multiple tetrahedrons through the triangulation algorithm;

[0025] The material volume is calculated by the formula WV=∑(Uj×Vj×Wj) / 6; wherein U, V and W represent the lengths of the three edges of the tetrahedron; j represents the number of the tetrahedron, j=1, 2, ..., N; N represents the total number of tetrahedrons; ∑ is the sum of j.

[0026] Furthermore, generating material point cloud data according to the parameter data and the transportation point cloud data comprises the following steps:

[0027] Step 1: Obtain the size data and shape data in the parameter data to establish a corresponding geometric model in three-dimensional space;

[0028] Step 2: Align and register the acquired transport point cloud data with the geometric model of the transport vehicle through the ICP algorithm;

[0029] Step 3: Use the 3D point cloud processing algorithm to cut the transportation point cloud data according to the boundary of the geometric model;

[0030] Step 4: extract the material accumulation point cloud data after cutting as material point cloud data, wherein the material point cloud data is point cloud data with the center position of the bottom of the transport truck bucket as the origin of the three-dimensional coordinates.

[0031] Furthermore, generating the material weight according to the material volume and comprehensive density includes:

[0032] Get the material volume WV and comprehensive density ZM corresponding to the transport vehicle ID;

[0033] The material weight WZ corresponding to the transport vehicle ID is calculated using the formula WZ=WV×ZM.

[0034] Furthermore, generating the material shedding coefficient according to the material point cloud data includes:

[0035] Get the three-dimensional coordinates of the highest point in the material point cloud data, including X, Y and Z, where Z represents the height, X represents the position of the three-dimensional coordinate in the forward direction of the transport vehicle, and Y represents the position of the three-dimensional coordinate in the width direction of the transport vehicle;

[0036] Determine whether the Z in the three-dimensional coordinates is greater than the height threshold;

[0037] Yes, mark the Z greater than the height threshold as JZ, and calculate the difference CJZ between JZ and the height threshold;

[0038] Get the absolute values ​​XJZ and YJZ of JZ corresponding to X and Y, as well as the length CCD and width CKD of the transport bucket;

[0039] When XJZ is less than the length threshold ω1, XJZ=ω1 / 2;

[0040] When YJZ is less than the width threshold ω2, YJZ=ω2 / 2;

[0041] The material shedding coefficient WTX is calculated by the formula;

[0042] WTX=1-exp(-(CJZ^β / DG+XJZ / ((CCD / 2)-XJZ)+YJZ / ((CKD / 2)-YJZ))); where β is the exponential coefficient, β>1; DG is the unit height;

[0043] No, the material shedding coefficient WTX=0.

[0044] This application compares the three-dimensional coordinates of the highest point in the material point cloud data with the center position of the bottom of the transport vehicle's cargo box, and calculates the material shedding coefficient during transportation through the position of the highest point. This can effectively remind management personnel of possible material shedding during transportation, avoid the possibility of accidents during transportation, and improve the safety of material transportation.

[0045] Furthermore, the generating of the warning signal according to the material shedding coefficient and the material weight includes:

[0046] Obtain material shedding coefficient and material weight;

[0047] When the material shedding coefficient is greater than the shedding threshold, a material shedding alarm signal is generated;

[0048] Otherwise, when the material shedding coefficient is greater than D times the shedding threshold, a material shedding warning signal is generated; otherwise, no operation is performed; where D is the proportional coefficient, D∈(0,1);

[0049] When the material weight is greater than the maximum weight threshold, a material overweight warning signal is generated; otherwise, no action is taken.

[0050] Another aspect of the present invention provides a method for weighing transport materials based on laser radar, comprising:

[0051] S0: Acquire transportation data; the transportation data includes a transportation vehicle ID and transportation point cloud data;

[0052] S1: preprocessing the transportation point cloud data to obtain preprocessed transportation point cloud data;

[0053] S2: Obtain the parameter data of the transport vehicle and the material data and comprehensive density of the transported material in the transport query table according to the transport vehicle ID; generate material point cloud data according to the parameter data and the transport point cloud data, and then calculate the material volume;

[0054] S3: Generate material weight based on material volume and comprehensive density; generate material shedding coefficient based on material point cloud data;

[0055] S4: Generate an early warning signal based on the material shedding coefficient and material weight; make corresponding prompts based on the early warning signal and contact the management personnel.

[0056] Compared with the prior art, the beneficial effects of this application are:

[0057] 1. This application obtains the parameter data of the transport vehicle and the material data and comprehensive density of the transported materials in the transport query table according to the transport vehicle ID; generates material point cloud data according to the parameter data and the transport point cloud data, and then calculates the material volume; generates material weight according to the material volume and comprehensive density; generates material shedding coefficient according to the material point cloud data; generates an early warning signal according to the material shedding coefficient and the material weight, and excludes the material volume of the container where the material is located when calculating the material volume, and considers that the densities of materials of different types and sizes in the transport bucket are different, and uses the comprehensive density instead of the material density and the net volume to calculate a more accurate material weight, thereby improving the accuracy of calculating the material weight when transporting materials.

[0058] 2. This application compares the three-dimensional coordinates of the highest point in the material point cloud data with the center position of the bottom of the transport vehicle's cargo box, and calculates the material shedding coefficient during transportation through the position of the highest point. This can effectively remind management personnel of possible material shedding during transportation, avoid the possibility of accidents during transportation, and improve the safety of material transportation. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0060] Figure 1 This is a schematic diagram of the principle of the laser radar-based transport material weighing system of this application;

[0061] Figure 2 Generate a flow chart for the early warning signal of this application;

[0062] Figure 3 This is a flow chart of the laser radar-based transport material weighing method of this application. DETAILED DESCRIPTION

[0063] The technical solution of the present application will be described clearly and completely in conjunction with the embodiments below. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application.

[0064] See also Figure 1 , the first aspect of the present application provides a laser radar-based transport material weighing system, including: a data acquisition module, a data processing module, a data analysis module, an early warning module and a database;

[0065] Data acquisition module: obtains transportation data through data acquisition equipment; transportation data includes transportation vehicle ID and transportation point cloud data; data acquisition equipment includes laser radar, etc., and transportation point cloud data refers to the point cloud data obtained by scanning the entire transportation vehicle through the laser radar;

[0066] Data processing module: preprocessing the transportation point cloud data to obtain preprocessed transportation point cloud data;

[0067] Data analysis module: Obtain the parameter data of the transport vehicle and the material data and comprehensive density of the transported materials in the transport query table according to the transport vehicle ID. The parameter data refers to the parameters of the transport vehicle itself, including the size data and shape data of the transport vehicle, etc. The material data includes the material type and material size; calculate the material volume after generating the material point cloud data according to the parameter data and the transport point cloud data. The material point cloud data refers to the point cloud data of the transported material excluding the container material when the material is loaded. The material volume refers to the net volume of the material; generate the material weight according to the material volume and comprehensive density. The material weight refers to the net weight of the material. The comprehensive density refers to the density of materials of different types and sizes in the container, not the density of the material itself; generate the material shedding coefficient according to the material point cloud data. The material shedding coefficient refers to the possible degree of material shedding during transportation; generate an early warning signal according to the material shedding coefficient and the material weight;

[0068] Early warning module: Make corresponding prompts according to the early warning signals and contact the management personnel. The early warning signals include material falling alarm signal, material falling warning signal and material overweight warning signal.

[0069] This embodiment obtains the parameter data of the transport vehicle and the material data and comprehensive density of the transported material in the transport query table according to the transport vehicle ID; generates material point cloud data according to the parameter data and the transport point cloud data, and then calculates the material volume; generates material weight according to the material volume and comprehensive density; generates material shedding coefficient according to the material point cloud data; generates an early warning signal according to the material shedding coefficient and the material weight, and excludes the material volume of the container where the material is located when calculating the material volume, and considers that the densities of materials of different types and sizes in the transport bucket are different, and uses the comprehensive density instead of the material density and the net volume to calculate a more accurate material weight, thereby improving the accuracy of calculating the material weight when transporting materials.

[0070] Data preprocessing includes denoising and downsampling operations;

[0071] Denoising operation: The point cloud data is filtered to remove noise points and obtain normal data. The filtering algorithms include mean filtering, median filtering and Gaussian filtering.

[0072] Downsampling operation: downsampling the normal data to obtain the preprocessed point cloud data; downsampling processing includes random sampling and voxelization.

[0073] The construction of the transport query table includes the following steps:

[0074] Obtain several transport vehicle IDs and their corresponding parameter data, material data and their corresponding comprehensive density; the comprehensive density changes with the type and size of the material loaded on the transport vehicle each time;

[0075] A transport query table is created with several transport vehicle IDs and their corresponding parameter data, material data and their corresponding comprehensive density.

[0076] The comprehensive density is generated from the material data, including:

[0077] Get material types and material size ranges from some historical material data;

[0078] Put materials of several material size ranges of material types into various containers, and obtain the net weight JZi and net volume Vi of the materials in various containers;

[0079] The comprehensive density ZMi corresponding to several different material sizes in the material category is calculated by the formula ZMi=JZi / Vi; wherein i represents the material number of several different material sizes in each material category, i=1, 2, …, M; M is the total number of different material sizes in the material category; when the container volume is determined, in the same material category, the gap between large-sized materials will be larger than the gap between small-sized materials, resulting in more space not being filled, resulting in the comprehensive density of large-sized materials being lower than the comprehensive density of small-sized materials; therefore, the comprehensive density of different material sizes is considered as an important factor in calculating the material weight; as the net weight increases, the comprehensive density will increase accordingly;

[0080] The comprehensive density of each material size range in several material types is composed into a comprehensive density table.

[0081] After generating material point cloud data based on parameter data and transportation point cloud data, calculate the material volume, including:

[0082] Obtain parameter data and transportation point cloud data;

[0083] Generate material point cloud data based on parameter data and transportation point cloud data;

[0084] Construct a triangular mesh model based on the material point cloud data, and divide the triangular mesh model into multiple tetrahedrons through a triangulation algorithm; the triangulation algorithm includes the Delaunay algorithm, etc.

[0085] The material volume is calculated using the formula WV=∑(Uj×Vj×Wj) / 6; wherein U, V and W represent the lengths of the three edges of a tetrahedron; j represents the number of the tetrahedron, j=1, 2,…, N; N represents the total number of tetrahedrons; ∑ is the sum of j; when the number of tetrahedrons is determined, as the lengths of the three edges of each tetrahedron increase, the material volume will also increase accordingly.

[0086] Generating material point cloud data according to parameter data and transportation point cloud data includes the following steps:

[0087] Step 1: Obtain the size data and shape data in the parameter data to establish a corresponding geometric model in three-dimensional space;

[0088] Step 2: Align and register the acquired transport point cloud data with the geometric model of the transport vehicle through the ICP algorithm;

[0089] Step 3: Use the 3D point cloud processing algorithm to cut the transportation point cloud data according to the boundary of the geometric model;

[0090] Step 4: Extract the material accumulation point cloud data after cutting as material point cloud data. The material point cloud data is point cloud data with the center position of the bottom of the transport truck bucket as the origin of the three-dimensional coordinates.

[0091] Generate material weight based on material volume and combined density, including:

[0092] Get the material volume WV and comprehensive density ZM corresponding to the transport vehicle ID;

[0093] The material weight WZ corresponding to the transport vehicle ID is calculated using the formula WZ=WV×ZM; the material weight will increase with the increase of the material volume and the material comprehensive density.

[0094] Generate material shedding coefficient based on material point cloud data, including:

[0095] Get the three-dimensional coordinates of the highest point in the material point cloud data, including X, Y and Z, where Z represents the height, X represents the position of the three-dimensional coordinate in the forward direction of the transport vehicle, and Y represents the position of the three-dimensional coordinate in the width direction of the transport vehicle;

[0096] Determine whether the Z in the three-dimensional coordinates is greater than the height threshold, which is set based on experience;

[0097] Yes, mark the Z greater than the height threshold as JZ, and calculate the difference CJZ between JZ and the height threshold;

[0098] Get the absolute values ​​XJZ and YJZ of JZ corresponding to X and Y, as well as the length CCD and width CKD of the transport bucket;

[0099] When XJZ is less than the length threshold ω1, XJZ=ω1 / 2;

[0100] When YJZ is less than the width threshold ω2, YJZ = ω2 / 2; the length threshold ω1 and the width threshold ω2 are set according to experience;

[0101] The material shedding coefficient WTX is calculated by the formula;

[0102] WTX=1-exp(-(CJZ^β / DG+XJZ / ((CCD / 2)-XJZ)+YJZ / ((CKD / 2)-YJZ))); wherein β is an exponential coefficient, β>1, and a specific value is set based on experience; DG is a unit height, and a specific value is set based on experience. In this embodiment, DG is set to 5 cm; when Z is higher than the height threshold, the material will fall off during transportation, and the closer the highest point is to the origin of the coordinate system, the smaller the possibility of falling off. On the contrary, when the highest point is closest to the edge of the transport vehicle, the possibility of falling off will increase. Therefore, as CJZ, XJZ and YJZ increase, the material falling coefficient WTX will increase accordingly.

[0103] No, the material shedding coefficient WTX=0.

[0104] This embodiment compares the three-dimensional coordinates of the highest point in the material point cloud data with the center position of the bottom of the transport vehicle's cargo box, and calculates the material shedding coefficient during transportation through the position of the highest point. This can effectively remind management personnel of possible material shedding during transportation, avoid the possibility of accidents during transportation, and improve the safety of material transportation.

[0105] See also Figure 2 , generate early warning signals based on the material shedding coefficient and material weight, including:

[0106] Obtain material shedding coefficient and material weight;

[0107] Determine whether the material shedding coefficient is greater than the shedding threshold. If yes, generate a material shedding alarm signal. The shedding threshold is set based on experience.

[0108] No, determine whether the material shedding coefficient is greater than D times the shedding threshold. If yes, generate a material shedding warning signal; No, do nothing; where D is the proportional coefficient, D∈(0,1), the specific value is set according to experience, and in this embodiment, D is set to 0.6;

[0109] Determine whether the material weight is greater than the maximum weight threshold. If yes, generate a material overweight warning signal, and the maximum weight threshold is set based on experience; if no, do nothing.

[0110] See also Figure 3 Another aspect of the present application provides a laser radar-based transport material weighing method, comprising:

[0111] S0: Obtain transportation data; transportation data includes transportation vehicle ID and transportation point cloud data;

[0112] S1: preprocessing the transportation point cloud data to obtain preprocessed transportation point cloud data;

[0113] S2: Obtain the parameter data of the transport vehicle and the material data and comprehensive density of the transported material in the transport query table according to the transport vehicle ID; generate material point cloud data according to the parameter data and the transport point cloud data, and then calculate the material volume;

[0114] S3: Generate material weight based on material volume and comprehensive density; generate material shedding coefficient based on material point cloud data;

[0115] S4: Generate an early warning signal based on the material shedding coefficient and material weight; make corresponding prompts based on the early warning signal and contact the management personnel.

[0116] Part of the data in the above formula is calculated by removing the dimension and taking its numerical value. The formula is a formula closest to the actual situation obtained by software simulation of a large amount of collected data; the preset parameters and preset thresholds in the formula are set by technical personnel in this field according to actual conditions or obtained through simulation of a large amount of data.

[0117] The working principle of the present application is as follows: obtaining transportation data through data acquisition equipment; preprocessing the transportation point cloud data to obtain preprocessed transportation point cloud data; obtaining the parameter data of the transportation vehicle and the material data and comprehensive density of the transportation material in the transportation query table according to the transportation vehicle ID; generating material point cloud data according to the parameter data and transportation point cloud data and then calculating the material volume; generating material weight according to the material volume and comprehensive density; generating material shedding coefficient according to the material point cloud data; generating an early warning signal according to the material shedding coefficient and the material weight; making corresponding prompts according to the early warning signal and contacting the management personnel, excluding the material volume of the container where the material is located when calculating the material volume, and considering the different densities of materials of different types and sizes in the transport bucket, using the comprehensive density instead of the material density and the net volume to calculate a more accurate material weight, thereby improving the accuracy of calculating the material weight when transporting materials, and avoiding the problem that the existing technology lacks consideration of the material volume of the bucket itself when calculating the material volume through laser radar scanning, so that the calculated material volume includes the material volume of the material, resulting in the net volume of the material being inaccurate, which in turn leads to the problem of low accuracy in calculating the material weight.

[0118] The above embodiments are only used to illustrate the technical method of the present application and are not intended to limit it. Although the present application has been described in detail with reference to the preferred embodiments, a person of ordinary skill in the art should understand that the technical method of the present application may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present application.

Claims

1. The transport material weighing system based on laser radar is characterized by: include: Data collection module, data processing module, data analysis module, early warning module and database; The data acquisition module is used to acquire transportation data through a data acquisition device; the transportation data includes a transportation vehicle ID and transportation point cloud data; The data processing module is used to preprocess the transport point cloud data to obtain preprocessed transport point cloud data; The data analysis module: obtains the parameter data of the transport vehicle and the material data and comprehensive density of the transported material in the transport query table according to the transport vehicle ID; generates material point cloud data according to the parameter data and the transport point cloud data, and then calculates the material volume; generates the material weight according to the material volume and comprehensive density; generates the material shedding coefficient according to the material point cloud data; generates an early warning signal according to the material shedding coefficient and the material weight; The early warning module: makes corresponding prompts according to the early warning signals and contacts the management personnel.

2. The laser radar-based transport material weighing system according to claim 1, characterized in that: The data preprocessing includes a denoising operation and a downsampling operation.

3. The laser radar-based transport material weighing system according to claim 1, characterized in that: The construction of the transport query table includes the following steps: Obtain several transport vehicle IDs and their corresponding parameter data, material data and their corresponding comprehensive density; A transport query table is created with several transport vehicle IDs and their corresponding parameter data, material data and their corresponding comprehensive density.

4. The laser radar-based transport material weighing system according to claim 3 is characterized in that: The comprehensive density is generated through material data, including: Get material types and material size ranges from some historical material data; Put materials of several material size ranges of material types into various containers, and obtain the net weight JZi and net volume Vi of the materials in various containers; The comprehensive density ZMi corresponding to several different material sizes in the material category is calculated by the formula ZMi=JZi / Vi; wherein i represents the material number of several different material sizes in each material category, i=1, 2, …, M; M is the total number of different material sizes in the material category; The comprehensive density of each material size range in several material types is composed into a comprehensive density table.

5. The laser radar-based transport material weighing system according to claim 1, characterized in that: The step of calculating the material volume after generating the material point cloud data according to the parameter data and the transportation point cloud data includes: Obtain parameter data and transportation point cloud data; Generate material point cloud data based on parameter data and transportation point cloud data; Construct a triangular mesh model based on the material point cloud data, and divide the triangular mesh model into multiple tetrahedrons through the triangulation algorithm; The material volume is calculated by the formula WV=∑(Uj×Vj×Wj) / 6; wherein U, V and W represent the lengths of the three edges of the tetrahedron; j represents the number of the tetrahedron, j=1, 2, ..., N; N represents the total number of tetrahedrons; ∑ is the sum of j.

6. The laser radar-based transport material weighing system according to claim 5, characterized in that: The method of generating material point cloud data according to parameter data and transportation point cloud data comprises the following steps: Step 1: Obtain the size data and shape data in the parameter data to establish a corresponding geometric model in three-dimensional space; Step 2: Align and register the acquired transport point cloud data with the geometric model of the transport vehicle through the ICP algorithm; Step 3: Use the 3D point cloud processing algorithm to cut the transportation point cloud data according to the boundary of the geometric model; Step 4: extract the material accumulation point cloud data after cutting as material point cloud data, wherein the material point cloud data is point cloud data with the center position of the bottom of the transport truck bucket as the origin of the three-dimensional coordinates.

7. The laser radar-based transport material weighing system according to claim 1, characterized in that: The method of generating the material weight according to the material volume and comprehensive density includes: Get the material volume WV and comprehensive density ZM corresponding to the transport vehicle ID; The material weight WZ corresponding to the transport vehicle ID is calculated using the formula WZ=WV×ZM.

8. The laser radar-based transport material weighing system according to claim 1, characterized in that: The method of generating a material shedding coefficient according to the material point cloud data includes: Get the three-dimensional coordinates of the highest point in the material point cloud data, including X, Y and Z, where Z represents the height, X represents the position of the three-dimensional coordinate in the forward direction of the transport vehicle, and Y represents the position of the three-dimensional coordinate in the width direction of the transport vehicle; Determine whether the Z in the three-dimensional coordinates is greater than the height threshold; Yes, mark the Z greater than the height threshold as JZ, and calculate the difference CJZ between JZ and the height threshold; Get the absolute values ​​XJZ and YJZ of JZ corresponding to X and Y, as well as the length CCD and width CKD of the transport bucket; When XJZ is less than the length threshold ω1, XJZ=ω1 / 2; When YJZ is less than the width threshold ω2, YJZ=ω2 / 2; The material shedding coefficient WTX is calculated by the formula; WTX=1-exp(-(CJZ^β / DG+XJZ / ((CCD / 2)-XJZ)+YJZ / ((CKD / 2)-YJZ))); where β is the exponential coefficient, β>1; DG is the unit height; No, the material shedding coefficient WTX=0.

9. The laser radar-based transport material weighing system according to claim 1, characterized in that: The generating of the warning signal according to the material shedding coefficient and the material weight includes: Obtain material shedding coefficient and material weight; When the material shedding coefficient is greater than the shedding threshold, a material shedding alarm signal is generated; Otherwise, when the material shedding coefficient is greater than D times the shedding threshold, a material shedding warning signal is generated; otherwise, no operation is performed; where D is the proportional coefficient, D∈(0,1); When the material weight is greater than the maximum weight threshold, a material overweight warning signal is generated; otherwise, no action is taken.

10. A laser radar-based transport material weighing method, applied to the laser radar-based transport material weighing method according to any one of claims 1 to 9, characterized in that: include: S0: Acquire transportation data; the transportation data includes a transportation vehicle ID and transportation point cloud data; S1: preprocessing the transportation point cloud data to obtain preprocessed transportation point cloud data; S2: Obtain the parameter data of the transport vehicle and the material data and comprehensive density of the transported material in the transport query table according to the transport vehicle ID; generate material point cloud data according to the parameter data and the transport point cloud data, and then calculate the material volume; S3: Generate material weight based on material volume and comprehensive density; generate material shedding coefficient based on material point cloud data; S4: Generate an early warning signal based on the material shedding coefficient and material weight; make corresponding prompts based on the early warning signal and contact the management personnel.

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