Automobile Coal Carriage Sampling Control Method, System, Computer Device and Storage Medium

Abstract

The present invention belongs to the field of coal sample quality monitoring, and discloses a sampling control method, system, computer device and storage medium for a coal carriage of an automobile, including: obtaining the weight of the coal in the current carriage and the carriage size information; obtaining the sampling number of the current carriage according to the weight of the coal in the current carriage and the preset sampling number per unit weight of the coal belonging to the current batch; obtaining each sampling coordinate when sampling according to the sampling number of the current carriage and the carriage size information; converting each sampling coordinate into each virtual sampling coordinate under the standard vehicle type size in turn according to the carriage size information and the preset standard vehicle type size information; obtaining the distribution characteristics of each virtual sampling coordinate, and determining whether there is a risk of sampling fraud according to the distribution characteristics of each virtual sampling coordinate. The problem of sampling representativeness is solved, uniform sampling of the entire coal batch is realized, the phenomenon that large vehicles pull low calorific value coal and small vehicles pull high calorific value coal is effectively prevented, and thus the quality of the entire batch of coal is effectively guaranteed.

Description

Technical Field

[0001] The present invention belongs to the field of coal sample quality monitoring, and relates to a sampling control method, system, computer device and storage medium for coal in a truck carriage. Background Art

[0002] Coal is the "ration" for most thermal power enterprises and is the basic raw material for generating electric energy. Its cost accounts for more than half of the total production and operation cost of thermal power enterprises. Therefore, starting from fuel management to achieve cost reduction and efficiency improvement has become the key work of domestic power generation enterprises. Fuel management is divided into two lines: the operating cost line and the production business line. Among them, the operating cost line aims at risk control and focuses on controlling procurement, in-plant weighing and quality inspection, etc. The production business line takes economic blending combustion as the starting point and focuses on optimizing procurement, storage and blending combustion search, etc.

[0003] Currently, among all coal delivery methods, the coal delivered by trucks is the most complex and the risks are the most prominent. Traditional power plants usually adopt a fixed-point mode for sampling coal delivered by trucks. Generally, two fixed points are set. In this way, the sampling weights of large and small trucks are the same during the coal quality sampling process. Suppliers take advantage of this loophole. Large trucks pull low-calorie coal and small trucks pull high-calorie coal. Although the calorific value meets the contract requirements during coal quality acceptance, the actual calorific value is low, resulting in economic losses for power plants. Summary of the Invention

[0004] The purpose of the present invention is to overcome the shortcoming of the risk of fraud in sampling coal in a truck carriage in the above-mentioned existing technology, and provide a sampling control method, system, computer device and storage medium for coal in a truck carriage.

[0005] To achieve the above purpose, the present invention adopts the following technical solutions:

[0006] In the first aspect of the present invention, a sampling control method for coal in a truck carriage includes:

[0007] Obtain the weight of the coal in the current carriage and the carriage size information; obtain the sampling number of the current carriage according to the weight of the coal in the current carriage and the preset unit weight sampling number of the coal of the batch to which the coal in the current carriage belongs; obtain each sampling coordinate when sampling according to the sampling number of the current carriage and the carriage size information; convert each sampling coordinate into each virtual sampling coordinate under the standard vehicle type size according to the carriage size information and the preset standard vehicle type size information; obtain the distribution characteristics of each virtual sampling coordinate, and determine whether there is a risk of sampling fraud according to the distribution characteristics of each virtual sampling coordinate.

[0008] Optionally, the obtaining of the weight of the coal in the current carriage and the carriage size information includes: obtaining the weight of the coal in the current carriage through the ore-out record IC card or the ore-out record two-dimensional code of the current carriage; obtaining the carriage size information through the radio frequency identification card of the current carriage.

[0009] Optionally, the preset unit weight sampling number of the coal of the batch to which the coal in the current carriage belongs is obtained by the following formula:

[0010] Unit weight sampling number = standard total number of points / ore shipment volume of the coal of the batch to which the coal in the current carriage belongs

[0011] Wherein, the standard total number of points = general analysis and common sample weight corresponding to the nominal maximum particle size on the coal of the batch to which the coal in the current carriage belongs ÷ weight of the sampling sub-sample.

[0012] Optionally, the obtaining of the sampling number of the current carriage according to the weight of the coal in the current carriage and the preset unit weight sampling number of the coal of the batch to which the coal in the current carriage belongs includes: according to the weight of the coal in the current carriage and the preset unit weight sampling number of the coal of the batch to which the coal in the current carriage belongs, obtaining the calculation result of the sampling number of the current carriage through the following formula: calculation result of the sampling number of the current carriage = weight of the coal in the current carriage × preset unit weight sampling number of the coal of the batch to which the coal in the current carriage belongs; when the calculation result of the sampling number of the current carriage is less than 1, the sampling number of the current carriage is 1; when the calculation result of the sampling number of the current carriage is greater than 1 and there is a decimal, obtaining the processing factor through the following formula: processing factor = decimal of the calculation result of the sampling number of the current carriage ÷ integer of the calculation result of the sampling number of the current carriage; when the processing factor is greater than the preset processing factor threshold, rounding up the calculation result of the sampling number of the current carriage to obtain the sampling number of the current carriage; otherwise, rounding down the calculation result of the sampling number of the current carriage to obtain the sampling number of the current carriage, and obtaining the remaining sampling coal amount through the following formula: remaining sampling coal amount = processing factor ÷ preset unit weight sampling number of the coal of the batch to which the coal in the current carriage belongs, and adding the remaining sampling coal amount to the weight of the coal in the next carriage of the coal of the batch to which the coal in the current carriage belongs.

[0013] Optionally, the preset processing factor threshold is 70%.

[0014] Optionally, the obtaining of the distribution characteristics of each virtual sampling coordinate and determining whether there is a sampling fraud risk according to the distribution characteristics of each virtual sampling coordinate includes: obtaining whether there is the same distribution law between each virtual sampling coordinate of the current carriage and the virtual sampling coordinates of other historical carriages of the coal of the batch to which the coal in the current carriage belongs. When there is the same distribution law, there is a fraud risk of non-random sampling; obtaining the distance of each virtual sampling coordinate from the carriage bottom plate. When the distances of all virtual sampling coordinates from the carriage bottom plate are greater than the preset distance threshold, there is a fraud risk of bottom coal laying.

[0015] Optionally, it further includes: establishing a coordinate system according to the standard vehicle model size information, combining each virtual sampling coordinate to establish a three-dimensional distribution map of sampling points, and visually displaying the three-dimensional distribution map of sampling points.

[0016] In the second aspect of the present invention, an automobile coal carriage sampling control system includes:

[0017] A first acquisition module for acquiring the weight of the coal in the current carriage and the carriage size information;

[0018] A sampling number determination module for obtaining the sampling number of the current carriage according to the weight of the coal in the current carriage and the preset unit weight sampling number of the batch of coal to which the coal in the current carriage belongs;

[0019] A second acquisition module for acquiring each sampling coordinate when sampling according to the sampling number of the current carriage and the carriage size information;

[0020] A coordinate conversion module for sequentially converting each sampling coordinate into each virtual sampling coordinate under the standard vehicle model size according to the carriage size information and the preset standard vehicle model size information;

[0021] A sampling risk analysis module for obtaining the distribution characteristics of each virtual sampling coordinate and determining whether there is a sampling fraud risk according to the distribution characteristics of each virtual sampling coordinate.

[0022] In the third aspect of the present invention, a computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the above-mentioned automobile coal carriage sampling control method are implemented.

[0023] In the fourth aspect of the present invention, a computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above-mentioned automobile coal carriage sampling control method are implemented.

[0024] Compared with the prior art, the present invention has the following beneficial effects:

[0025] The sampling control method for the coal compartment of a motor vehicle in the present invention generates the number of sampling points based on the weight of the coal in the current compartment and the preset number of sampling per unit weight of the coal belonging to the current batch, effectively solving the problem of sampling representativeness, achieving uniform sampling for the entire batch of coal, effectively preventing the phenomenon that large vehicles carry low-calorie coal and small vehicles carry high-calorie coal, and thus effectively ensuring the quality of the entire batch of coal. At the same time, the sampling coordinates during sampling are obtained according to the number of samples in the current compartment and the compartment size information, and the sampling coordinates are sequentially converted into virtual sampling coordinates under the standard vehicle model size. Then, according to the distribution characteristics of the virtual sampling coordinates, it is determined whether there is a risk of sampling fraud, and hidden fraud behaviors can be detected in a timely manner, strengthening the technical measures for risk control. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a flowchart of the sampling control method for the coal compartment of a motor vehicle according to an embodiment of the present invention;

[0027] Figure 2 It is a three-dimensional distribution diagram of sampling points according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0028] In order to enable those skilled in the art to better understand the solution of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative work shall fall within the protection scope of the present invention.

[0029] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily need to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device comprising a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0030] The present invention will be further described in detail below in conjunction with the accompanying drawings:

[0031] See Figure 1, in an embodiment of the present invention, a sampling control method for a coal compartment of a vehicle is provided to solve the problem of sampling representativeness in the process of coal quality acceptance for power plant vehicles entering the factory. At the same time, potential risks are discovered through data analysis, the coal quality acceptance ability is improved, and economic losses are avoided. Specifically, the method includes the following steps:

[0032] S1: Obtain the weight of the coal in the current compartment and the compartment size information.

[0033] S2: According to the weight of the coal in the current compartment and the preset number of samples per unit weight of the coal in the batch to which the coal in the current compartment belongs, obtain the number of samples for the current compartment.

[0034] S3: Obtain each sampling coordinate when sampling according to the number of samples for the current compartment and the compartment size information.

[0035] S4: According to the compartment size information and the preset standard vehicle model size information, sequentially convert each sampling coordinate into each virtual sampling coordinate under the standard vehicle model size.

[0036] S5: Obtain the distribution characteristics of each virtual sampling coordinate, and determine whether there is a risk of sampling fraud according to the distribution characteristics of each virtual sampling coordinate.

[0037] The sampling control method for the coal compartment of a vehicle in the present invention generates the number of sampling points based on the weight of the coal in the current compartment and the preset number of samples per unit weight of the coal in the batch to which the coal in the current compartment belongs, effectively solving the problem of sampling representativeness, realizing uniform sampling of the entire coal batch, effectively preventing the phenomenon of large vehicles pulling low-calorie coal and small vehicles pulling high-calorie coal, and thus effectively ensuring the quality of the entire batch of coal. At the same time, each sampling coordinate when sampling according to the number of samples for the current compartment and the compartment size information is obtained, and each sampling coordinate is sequentially converted into each virtual sampling coordinate under the standard vehicle model size, and then whether there is a risk of sampling fraud is determined according to the distribution characteristics of each virtual sampling coordinate, which can timely discover hidden fraud behaviors and strengthen the risk control technical measures.

[0038] In a possible implementation manner, in the step S1, obtaining the weight of the coal in the current compartment and the compartment size information includes: obtaining the weight of the coal in the current compartment through the out-of-mine record IC card or out-of-mine record two-dimensional code of the current compartment; obtaining the compartment size information through the radio frequency identification card of the current compartment.

[0039] Specifically, the carriage dimension information generally includes the length, width, floor height of the carriage, and the position of the stiffeners. The carriage dimension information is a basic element for completing the carriage sampling and an important node for risk control. Therefore, in addition to requiring on-site supervision and signatures for the collection of carriage dimension information, it can also be officially launched after being reviewed. In addition, information such as RFID (Radio Frequency Identification) cards for identifying vehicle identities can be registered, and vehicle identification cards can be issued to the vehicles, and then the carriage dimension information can be obtained based on the radio frequency identification cards.

[0040] When the vehicle is discharging ore, the supplier and the ore shipment volume are recorded by means of an ore discharge record IC card or an ore discharge record QR code. In the process of ticket inspection upon entering the factory, in addition to identifying the supplier, the weight of the coal in the current carriage is identified.

[0041] In a possible implementation manner, in step S2, the preset sampling number per unit weight of the coal in the current carriage belonging to the batch of coal is obtained through the following formula: Sampling number per unit weight = Standard total number of points / Ore shipment volume of the coal in the current carriage belonging to the batch of coal; where, Standard total number of points = General analysis and shared sample weight corresponding to the nominal maximum particle size on the coal in the current carriage belonging to the batch of coal ÷ Sampling subsample weight, generally with tons as the unit of mass.

[0042] Specifically, obtaining the sampling number of the current carriage according to the weight of the coal in the current carriage and the preset sampling number per unit weight of the coal in the current carriage belonging to the batch of coal includes: According to the weight of the coal in the current carriage and the preset sampling number per unit weight of the coal in the current carriage belonging to the batch of coal, the calculation result of the sampling number of the current carriage is obtained through the following formula: Calculation result of the sampling number of the current carriage = Weight of the coal in the current carriage × Preset sampling number per unit weight of the coal in the current carriage belonging to the batch of coal; when the calculation result of the sampling number of the current carriage is less than 1, the sampling number of the current carriage is 1; when the calculation result of the sampling number of the current carriage is greater than 1 and there is a decimal, the following formula is used to obtain the processing factor: Processing factor = Decimal of the calculation result of the sampling number of the current carriage ÷ Integer of the calculation result of the sampling number of the current carriage; when the processing factor is greater than the preset processing factor threshold, the calculation result of the sampling number of the current carriage is rounded up to obtain the sampling number of the current carriage; otherwise, the calculation result of the sampling number of the current carriage is rounded down to obtain the sampling number of the current carriage, and the remaining sampling coal volume is obtained through the following formula: Remaining sampling coal volume = Processing factor ÷ Preset sampling number per unit weight of the coal in the current carriage belonging to the batch of coal, and the remaining sampling coal volume is added to the weight of the coal in the next carriage of the coal in the current carriage belonging to the batch of coal.

[0043] For the coal delivered by trucks, the daily coal intake is controlled using the daily coal delivery plan. Besides reasonably arranging the unloading work through the plan, the sampling number of the current carriage can be calculated based on the weight of the coal in the current carriage, general analysis, the weight of the shared sample, and the weight of the sampling sub-sample, so as to achieve the goal of different trucks and cars being allocated different sampling point numbers according to the coal delivery weight, realize uniform sampling, and thus solve the problem of sampling representativeness.

[0044] Among them, the preset processing factor threshold can be set to 70%. Compare the processing factor with 70%. When it is greater than or equal to, round up. When it is less than, the remaining coal quantity should be added to the weight of the coal in the next carriage. The next carriage recalculates the actual sampling point number with the newly calculated weight of the coal in the carriage.

[0045] In a possible implementation manner, in step S3, obtain each sampling coordinate when sampling according to the sampling number of the current carriage and the carriage size information. The sampling coordinate is a truck sampling machine, and a bridge sampling machine can be used. Perform random sampling according to the sampling number of the current carriage and the carriage size information, and feedback the sampling coordinates of each sampling point.

[0046] In a possible implementation manner, in step S4, the specific process of converting each sampling coordinate into each virtual sampling coordinate under the standard vehicle model size according to the carriage size information and the preset standard vehicle model size information includes: according to the feedback of each sampling coordinate (x, y, z), convert it to the standard vehicle model. Pull the scale to be even for statistical analysis. In this implementation manner, the preset standard vehicle model size is as follows: The X coordinate is the length of the factory carriage, and its range is 0 - 1200 mm. The Y coordinate is the width of the factory carriage, and its range is 0 - 240 mm. The Z coordinate is the height of the carriage, and its range is 0 - 180 mm. The conversion formula is as follows:

[0047] X' = (x / the length of the current carriage) * 1200 mm

[0048] Y' = (y / the width of the current carriage) * 240 mm

[0049] Z' = (z - the height of the bottom of the current carriage) / 10 cm

[0050] Each sampling coordinate (x, y, z) is converted into each virtual coordinate (X', Y', Z').

[0051] In a possible implementation manner, in step S5, obtaining the distribution characteristics of each virtual sampling coordinate and determining whether there is a sampling fraud risk according to the distribution characteristics of each virtual sampling coordinate includes: obtaining whether there is the same distribution law between each virtual sampling coordinate of the current carriage and the virtual sampling coordinates of other historical carriages of the coal of the same batch in the current carriage. When there is the same distribution law, there is a fraud risk of non-random sampling; obtaining the distance between each virtual sampling coordinate and the carriage bottom plate. When the distances between each virtual sampling coordinate and the carriage bottom plate are all greater than a preset distance threshold, there is a fraud risk of bottom coal.

[0052] Specifically, when obtaining the distribution characteristics of each virtual sampling coordinate, the standard vehicle model size is pre-divided into several regions in the (X, Y) directions, which can be divided into 18 regions, and the region numbers to which each virtual coordinate (X', Y', Z') belongs are marked. Then, for the distribution law in sequence, it is determined whether there is the same distribution law between each virtual sampling coordinate of the current carriage and the virtual sampling coordinates of other historical carriages of the coal of the same batch in the current carriage.

[0053] At the same time, for the distance between each virtual sampling coordinate and the carriage bottom plate, the distance can be divided into several intervals, and the number of virtual sampling coordinates in each interval is counted at each point to determine whether full-section sampling has been performed.

[0054] In a possible implementation manner, see Figure 2 The sampling control method for the coal carriage of the vehicle further includes: establishing a coordinate system according to the standard vehicle model size information, combining each virtual sampling coordinate to establish a three-dimensional distribution map of sampling points, and visually displaying the three-dimensional distribution map of sampling points. Specifically, the three-dimensional distribution map of sampling points can also be divided into several regions, and different colors are set for the virtual sampling coordinates in different regions. For example, a color with a large color difference from other regions can be set for the key attention area to enhance the contrast and facilitate intuitive information acquisition.

[0055] Taking an actual case as an example: the carriage horizontal plane is divided into 18 regions according to coordinates. After converting the actual horizontal coordinates X and Y into virtual coordinates (X', Y'), the actual sampling points are assigned to the corresponding regions. Finally, through multiple dimensions such as time, supplier, mine, coal type, and departure station, the number of points in each region and the proportional relationship to the total number of points can be statistically analyzed, so as to judge the randomness of the sampling points. After converting the actual depth coordinate Z into a virtual coordinate (Z'), it is compared with the height difference of the carriage bottom plate in the system and classified into the following difference intervals. Finally, through multiple dimensions such as time, supplier, mine, coal type, and departure station, the number of points in each interval and the proportional relationship to the total number of points can be statistically analyzed, so as to analyze the sampling depth and discover the potential risk of bottom coal. As shown in Table 1 below.

[0056] Table 1 Randomness table of sampling point distribution

[0057]

[0058]

[0059] The following is an apparatus embodiment of the present invention, which can be used to implement the method embodiment of the present invention. For details not disclosed in the apparatus embodiment, please refer to the method embodiment of the present invention.

[0060] In another embodiment of the present invention, a sampling control system for a coal truck carriage is provided, which can be used to implement the above-mentioned sampling control method for a coal truck carriage. Specifically, the sampling control system for a coal truck carriage includes a first acquisition module, a sampling number determination module, a second acquisition module, a coordinate conversion module, and a sampling risk analysis module.

[0061] Among them, the first acquisition module is used to acquire the weight of the coal in the current carriage and the carriage size information; the sampling number determination module is used to obtain the sampling number of the current carriage according to the weight of the coal in the current carriage and the preset unit weight sampling number of the coal in the current carriage belonging to the same batch; the second acquisition module is used to acquire each sampling coordinate when sampling according to the sampling number of the current carriage and the carriage size information; the coordinate conversion module is used to convert each sampling coordinate into each virtual sampling coordinate under the standard vehicle type size in turn according to the carriage size information and the preset standard vehicle type size information; the sampling risk analysis module acquires the distribution characteristics of each virtual sampling coordinate, and determines whether there is a sampling fraud risk according to the distribution characteristics of each virtual sampling coordinate.

[0062] In a possible implementation manner, the acquiring the weight of the coal in the current carriage and the carriage size information includes: acquiring the weight of the coal in the current carriage through the outgoing mine record IC card or the outgoing mine record two-dimensional code of the current carriage; acquiring the carriage size information through the radio frequency identification card of the current carriage.

[0063] In a possible implementation manner, the preset unit weight sampling number of the coal in the current carriage belonging to the same batch is obtained by the following formula: unit weight sampling number = standard total number of points / ore output of the coal in the current carriage belonging to the same batch, where the standard total number of points = weight of the general analysis and common test sample corresponding to the nominal maximum particle size on the coal in the current carriage belonging to the same batch ÷ weight of the sampling sub-sample.

[0064] In a possible implementation manner, obtaining the sampling number of the current carriage according to the weight of the coal in the current carriage and the preset sampling number per unit weight of the coal in the batch to which the coal in the current carriage belongs includes: according to the weight of the coal in the current carriage and the preset sampling number per unit weight of the coal in the batch to which the coal in the current carriage belongs, obtaining the calculation result of the sampling number of the current carriage through the following formula: the calculation result of the sampling number of the current carriage = the weight of the coal in the current carriage × the preset sampling number per unit weight of the coal in the batch to which the coal in the current carriage belongs; when the calculation result of the sampling number of the current carriage is less than 1, the sampling number of the current carriage is 1; when the calculation result of the sampling number of the current carriage is greater than 1 and there is a decimal, obtaining the processing factor through the following formula: the processing factor = the decimal of the calculation result of the sampling number of the current carriage ÷ the integer of the calculation result of the sampling number of the current carriage; when the processing factor is greater than the preset processing factor threshold, rounding up the calculation result of the sampling number of the current carriage to obtain the sampling number of the current carriage; otherwise, rounding down the calculation result of the sampling number of the current carriage to obtain the sampling number of the current carriage, and obtaining the remaining sampling coal amount through the following formula: the remaining sampling coal amount = the processing factor ÷ the preset sampling number per unit weight of the coal in the batch to which the coal in the current carriage belongs, and adding the remaining sampling coal amount to the weight of the coal in the next carriage of the batch to which the coal in the current carriage belongs.

[0065] In a possible implementation manner, the preset processing factor threshold is 70%.

[0066] In a possible implementation manner, obtaining the distribution characteristics of each virtual sampling coordinate, and determining whether there is a sampling fraud risk according to the distribution characteristics of each virtual sampling coordinate includes: obtaining whether there is the same distribution law between each virtual sampling coordinate of the current carriage and the virtual sampling coordinates of other historical carriages of the batch to which the coal in the current carriage belongs. When there is the same distribution law, there is a fraud risk of non-random sampling; obtaining the distance of each virtual sampling coordinate from the carriage bottom plate. When the distances of all virtual sampling coordinates from the carriage bottom plate are greater than the preset distance threshold, there is a fraud risk of bottom coal laying.

[0067] In a possible implementation manner, it further includes a visualization module, which is used to establish a coordinate system according to the standard vehicle model size information, combine each virtual sampling coordinate to establish a three-dimensional distribution map of sampling points, and visually display the three-dimensional distribution map of sampling points.

[0068] All relevant contents of each step involved in the embodiments of the foregoing method for controlling coal sampling in a vehicle carriage can be cited in the function descriptions of the corresponding functional modules of the system for controlling coal sampling in a vehicle carriage in the embodiments of the present invention, and will not be elaborated here.

[0069] In the embodiments of the present invention, the division of modules is illustrative and is only a logical function division. In actual implementation, there may be other division methods. In addition, in each embodiment of the present invention, each functional module may be integrated in a processor, may exist independently physically, or two or more modules may be integrated in one module. The above integrated modules may be implemented in the form of hardware or in the form of software functional modules.

[0070] In another embodiment of the present invention, a computer device is provided. The computer device includes a processor and a memory. The memory is used to store a computer program, and the computer program includes program instructions. The processor is used to execute the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or may also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, and is suitable for implementing one or more instructions. Specifically, it is suitable for loading and executing one or more instructions in the computer storage medium to implement the corresponding method flow or corresponding function. The processor described in the embodiments of the present invention may be used for the operation of the method for controlling the sampling of coal carriages in a vehicle.

[0071] In another embodiment of the present invention, a storage medium is also provided, specifically a computer-readable storage medium (Memory). The computer-readable storage medium is a memory device in a computer device and is used to store programs and data. It can be understood that the computer-readable storage medium here may include both the built-in storage medium in the computer device and, of course, the extended storage medium supported by the computer device. The computer-readable storage medium provides a storage space that stores the operating system of the terminal. And, in this storage space, one or more instructions suitable for being loaded and executed by the processor are also stored. These instructions may be one or more computer programs (including program codes). It should be noted that the computer-readable storage medium here may be a high-speed RAM memory or a non-volatile memory, such as at least one disk memory. One or more instructions stored in the computer-readable storage medium can be loaded and executed by the processor to implement the corresponding steps of the method for controlling the sampling of coal carriages in a vehicle in the above embodiments.

[0072] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0073] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to the embodiments of the present invention. It should be understood that each flow and / or block in the flowchart and / or block diagram, as well as the combination of flows and / or blocks in the flowchart and / or block diagram, can be realized by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for realizing the functions specified in one Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0074] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including instruction means that realizes the functions specified in one Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0075] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for realizing the functions specified in one Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0076] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that it is still possible to modify the specific implementation manners of the present invention or make equivalent replacements. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the protection scope of the claims of the present invention.

Claims

1. A method for sampling control and management of a coal carriage of an automobile, characterized in that, Including: Obtain the weight of the coal in the current carriage and the information of the carriage size; Obtain the sampling number of the current carriage according to the weight of the coal in the current carriage and the preset sampling number per unit weight of the coal in the batch to which the coal in the current carriage belongs; Obtain each sampling coordinate when sampling according to the sampling number of the current carriage and the carriage size information; According to the carriage size information and the preset standard vehicle type size information, sequentially convert each sampling coordinate into each virtual sampling coordinate under the standard vehicle type size; Obtain the distribution characteristics of each virtual sampling coordinate, and determine whether there is a risk of sampling fraud according to the distribution characteristics of each virtual sampling coordinate; The obtaining the distribution characteristics of each virtual sampling coordinate and determining whether there is a risk of sampling fraud according to the distribution characteristics of each virtual sampling coordinate includes: Obtain whether there is the same distribution law between each virtual sampling coordinate of the current carriage and the virtual sampling coordinates of other historical carriages of the coal in the batch to which the coal in the current carriage belongs. When there is the same distribution law, there is a risk of fraud in non-random sampling; Obtain the distance of each virtual sampling coordinate from the carriage bottom plate. When the distances of all virtual sampling coordinates from the carriage bottom plate are greater than the preset distance threshold, there is a risk of fraud in bottom coal laying; 2. The method for sampling and control of the coal carriage of an automobile according to claim 1, wherein The obtaining the weight of the coal in the current carriage and the carriage size information includes: Obtain the weight of the coal in the current carriage through the ore-out record IC card or the ore-out record two-dimensional code of the current carriage; obtain the carriage size information through the radio frequency identification card of the current carriage.

3. The method for sampling and control of a coal carriage of an automobile according to claim 1, wherein The preset sampling number per unit weight of the coal in the batch to which the coal in the current carriage belongs is obtained by the following formula: Sampling number per unit weight = standard total number of points / ore shipment volume of the coal in the batch to which the coal in the current carriage belongs. Among them, the standard total number of points = the weight of the general analysis and common test sample corresponding to the nominal maximum particle size of the coal in the batch to which the coal in the current carriage belongs ÷ the weight of the sampling sub-sample.

4. The method for sampling and control of the coal carriage of an automobile according to claim 1, characterized in that, The obtaining the sampling number of the current carriage according to the weight of the coal in the current carriage and the preset sampling number per unit weight of the coal in the batch to which the coal in the current carriage belongs includes: According to the weight of the coal in the current carriage and the preset sampling number per unit weight of the coal in the batch to which the coal in the current carriage belongs, obtain the calculation result of the sampling number of the current carriage through the following formula: Calculation result of the sampling number of the current carriage = weight of the coal in the current carriage × preset sampling number per unit weight of the coal in the batch to which the coal in the current carriage belongs; When the calculation result of the sampling number of the current carriage is less than 1, the sampling number of the current carriage is 1; When the calculation result of the sampling number of the current carriage is greater than 1 and there is a decimal, obtain the processing factor through the following formula: Processing factor = decimal of the calculation result of the sampling number of the current carriage ÷ integer of the calculation result of the sampling number of the current carriage; when the processing factor is greater than the preset processing factor threshold, round up the calculation result of the sampling number of the current carriage to obtain the sampling number of the current carriage; otherwise, round down the calculation result of the sampling number of the current carriage to obtain the sampling number of the current carriage. Obtain the remaining sampling coal volume through the following formula: Remaining sampling coal volume = processing factor ÷ preset sampling number per unit weight of the coal in the batch to which the coal in the current carriage belongs, and add the remaining sampling coal volume to the weight of the coal in the next carriage of the coal in the batch to which the coal in the current carriage belongs.

5. The method for sampling control of the coal carriage of an automobile according to claim 4, wherein The preset processing factor threshold is 70%.

6. The method for sampling control of the coal carriage of an automobile according to claim 1, wherein, It further includes: Establish a coordinate system according to the standard vehicle model size information, combine the virtual sampling coordinates to establish a three-dimensional distribution map of sampling points, and visually display the three-dimensional distribution map of sampling points.

7. A sampling control system for a coal carriage of an automobile, characterized in that, It includes: A first acquisition module for acquiring the weight of the coal in the current carriage and the carriage size information; A sampling number determination module for obtaining the sampling number of the current carriage according to the weight of the coal in the current carriage and the preset unit weight sampling number of the coal in the batch to which the coal in the current carriage belongs; A second acquisition module for acquiring each sampling coordinate during sampling according to the sampling number of the current carriage and the carriage size information; A coordinate conversion module for sequentially converting each sampling coordinate into each virtual sampling coordinate under the standard vehicle model size according to the carriage size information and the preset standard vehicle model size information; A sampling risk analysis module for obtaining the distribution characteristics of each virtual sampling coordinate and determining whether there is a sampling fraud risk according to the distribution characteristics of each virtual sampling coordinate; The obtaining of the distribution characteristics of each virtual sampling coordinate and determining whether there is a sampling fraud risk according to the distribution characteristics of each virtual sampling coordinate includes: Obtaining whether there is the same distribution law between the virtual sampling coordinates of the current carriage and the virtual sampling coordinates of other historical carriages of the coal in the batch to which the coal in the current carriage belongs. When there is the same distribution law, there is a fraud risk of non-random sampling; Obtaining the distance of each virtual sampling coordinate from the carriage bottom plate. When the distances of all virtual sampling coordinates from the carriage bottom plate are greater than the preset distance threshold, there is a fraud risk of bottom coal.

8. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method for controlling the sampling of the coal carriage of an automobile according to any one of claims 1 to 6.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the method for controlling the sampling of the coal carriage of an automobile according to any one of claims 1 to 6.

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