Vehicle sampling method and device

Abstract

The embodiment of the invention provides a vehicle sampling method and device. The vehicle sampling method comprises the steps that historical sampling information and reference proportion information corresponding to a target coal type are acquired; based on the historical sampling information, predicting a predicted increased vehicle number of target time; determining the congestion state of the current sampling channel at the target time according to the number of the vehicles waiting for sampling in the current sampling channel and the predicted increased number of the vehicles; and under the condition that the congestion state is congestion, based on the number of the vehicles waiting for mining, the number of the predicted increased vehicles and the reference proportion information, a current sampling proportion is adjusted, a target sampling proportion is determined, and the target sampling proportion is used for sampling the coal transport vehicles. The sampling proportion is adjusted by acquiring the congestion condition of the predicted sampling channel, so that traffic jam can be avoided while the sample quality is ensured, and the sampling efficiency is improved.

Description

Technical Field

[0001] The embodiments of this specification relate to the field of sampling technology, and more particularly to a vehicle sampling method and device. Background Art

[0002] As a transit place for centralized coal shipment, the dispatch station will randomly sample the vehicles transporting the coal to test the quality of the coal in order to ensure the quality of the purchased coal transported by truck. The traditional sampling ratio is set by the laboratory personnel in the dispatch station according to their experience and the coal supplier purchased. After the sampling ratio is set, the vehicles are concentrated. When a traffic jam occurs in the dispatch station, the colleagues in the transportation department are contacted by phone to adjust the sampling ratio. This method is inefficient, and it is difficult and inflexible to change the sampling ratio during the artificial setting. Therefore, it is urgent to provide a method to solve the above technical problems. Summary of the invention

[0003] In view of this, an embodiment of this specification provides a vehicle sampling method. One or more embodiments of this specification also relate to a vehicle sampling device, a computing device, a computer-readable storage medium and a computer program to solve the technical defects existing in the prior art.

[0004] According to a first aspect of an embodiment of this specification, a vehicle sampling method is provided, comprising: Obtain historical sampling information and reference ratio information corresponding to the target coal type; Based on the historical sampling information, predict the expected increase in the number of vehicles at the target time; Determine the congestion state of the current sampling channel at the target time according to the number of waiting vehicles in the current sampling channel and the expected number of additional vehicles; When the congestion state is congested, the current sampling ratio is adjusted based on the number of waiting vehicles, the expected number of additional vehicles and the reference ratio information to determine the target sampling ratio, wherein the target sampling ratio is used to sample coal transport vehicles.

[0005] According to a second aspect of an embodiment of this specification, a vehicle sampling device is provided, comprising: The data acquisition module 402 is configured to acquire historical sampling information and reference ratio information corresponding to the target coal type; The data calculation module 404 is configured to predict the expected increase in the number of vehicles at the target time based on the historical sampling information; The state determination module 406 is configured to determine the congestion state of the current sampling channel at the target time according to the number of waiting vehicles in the current sampling channel and the expected number of additional vehicles; The sampling module 408 is configured to adjust the current sampling ratio and determine the target sampling ratio based on the number of waiting vehicles, the expected number of additional vehicles and the reference ratio information when the congestion state is congestion, wherein the target sampling ratio is used to sample coal transport vehicles.

[0006] According to a third aspect of an embodiment of this specification, a computing device is provided, including: Memory and processor; The memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions. When the computer executable instructions are executed by the processor, the steps of the above-mentioned vehicle sampling method are implemented.

[0007] According to a fourth aspect of the embodiments of this specification, a computer-readable storage medium is provided, which stores computer-executable instructions, and when the instructions are executed by a processor, the steps of the above-mentioned vehicle sampling method are implemented.

[0008] An embodiment of the present specification obtains historical sampling information and reference ratio information of the target coal type, predicts the expected increase in the number of vehicles at the target time based on the historical sampling information, judges the congestion state of the current sampling channel at the target time based on the expected increase in the number of vehicles and the number of vehicles waiting for sampling in the current sampling channel, and automatically adjusts the current sampling ratio in the case of congestion according to the number of vehicles waiting for sampling, the expected increase in the number of vehicles and the reference ratio information to obtain the target sampling ratio, and samples coal transport vehicles according to the target sampling ratio, so that the sampling ratio meets the sampling ratio range set by the supplier while avoiding vehicle congestion as much as possible, thereby improving sampling efficiency, and the entire sampling ratio adjustment process is automatically implemented, effectively reducing labor costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1 is a flow chart of a vehicle sampling method provided by one embodiment of this specification; Figure 2A This is a first processing flow chart of a vehicle sampling method in a coal transportation yard provided by an embodiment of this specification, steps 202 to 216; Figure 2B This is a first processing flow chart of a vehicle sampling method in a coal transportation yard provided by an embodiment of this specification, steps 208 to 236; Figure 3A It is a second processing flow chart of a vehicle sampling method in a coal transportation yard provided by an embodiment of this specification, steps 302 to 330; Figure 3B It is a second processing flow chart of a vehicle sampling method in a coal transportation yard provided by an embodiment of this specification, steps 332 to 368; Figure 4 It is a structural schematic diagram of a vehicle sampling device provided by an embodiment of this specification; Figure 5 It is a structural block diagram of a computing device provided by an embodiment of this specification. DETAILED DESCRIPTION

[0010] Many specific details are described in the following description to facilitate a full understanding of this specification. However, this specification can be implemented in many other ways than those described herein, and those skilled in the art can make similar generalizations without violating the connotation of this specification, so this specification is not limited to the specific implementation disclosed below.

[0011] The terms used in one or more embodiments of this specification are only for the purpose of describing specific embodiments, and are not intended to limit one or more embodiments of this specification. The singular forms of "a", "said" and "the" used in one or more embodiments of this specification and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used in one or more embodiments of this specification refers to and includes any or all possible combinations of one or more associated listed items.

[0012] It should be understood that although the terms first, second, etc. may be used to describe various information in one or more embodiments of this specification, this information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of one or more embodiments of this specification, the first may also be referred to as the second, and similarly, the second may also be referred to as the first. Depending on the context, the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0013] In addition, it should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in one or more embodiments of this specification are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0014] During the transportation of coal, the dispatching station, as a transit place for the centralized dispatch of coal, will randomly sample the vehicles transporting coal to test the quality of the coal in order to ensure the quality of the purchased coal transported by road. In the past, the sampling ratio was set by the staff of the laboratory in the dispatching station based on experience and the purchase agreement with the coal supplier. After the vehicles arrive in batches, if there is congestion at the dispatching station, the laboratory staff needs to communicate with colleagues in the transportation department by phone to adjust the sampling ratio. This method is inefficient, and it is difficult to change the sampling ratio in the process of manually setting it, and it lacks flexibility. In addition, during holidays or special weather, the sampling efficiency is affected, which can easily lead to insufficient number of sample samples.

[0015] To this end, in this specification, a vehicle sampling method is provided. This specification also relates to a vehicle sampling device, a computing device, and a computer-readable storage medium, which are described in detail one by one in the following embodiments.

[0016] See also Figure 1 , Figure 1 A flow chart of a vehicle sampling method provided according to an embodiment of the present specification is shown, which specifically includes the following steps.

[0017] Step 102: Obtain historical sampling information and reference ratio information corresponding to the target coal type.

[0018] Specifically, the target coal type refers to the coal type that currently needs to adjust the sampling ratio and sample. One target coal type can be sampled by one or more target samplers. Each target sampler is correspondingly arranged in a sampling channel. Coal transport vehicles entering the shipping station need to enter the sampling channel for sampling before they can unload coal. Historical sampling information refers to the historical sampling data corresponding to the target coal type, including but not limited to the historical round-trip time of coal transport vehicles corresponding to the target coal type, and the sampling efficiency of the target sampler for sampling the target coal type. Reference ratio information refers to the relevant reference information for limiting the sampling ratio set by the laboratory personnel of the shipping station for the target coal type based on experience or after consultation with the supplier corresponding to the target coal type.

[0019] Based on this, in order to accurately predict whether there will be a traffic jam in the current sampling channel, it is necessary to first obtain the historical sampling information and reference ratio information corresponding to the target coal type. This information helps to analyze the law of vehicle arrival and the time consumption of the sampling process, and provides a basis for the subsequent adjustment of the sampling ratio.

[0020] Step 104: Based on the historical sampling information, predict the expected increase in the number of vehicles at the target time.

[0021] Specifically, the target time is a time point after the current time. The expected number of additional vehicles refers to the total number of vehicles added at the target time.

[0022] Based on this, the system can analyze the historical operating patterns of coal transport vehicles and the historical sampling patterns of target samplers according to historical sampling information, and predict the expected increase in the number of vehicles within the target time based on the analysis results.

[0023] In summary, through comprehensive analysis of historical data, the system can more scientifically predict the trend of future vehicle arrivals, providing strong data support for the formulation and adjustment of sampling plans.

[0024] Furthermore, in order to more accurately predict the number of vehicles expected to increase at the target time, the historical sampling information includes the target sampling efficiency of the target sampling machine and the round-trip time of the coal transport vehicles in transit; accordingly, the prediction of the expected number of vehicles to increase at the target time based on the historical sampling information includes: calculating the expected number of sampling vehicles of the target sampling machine within the preset time interval according to the preset time interval and the target sampling efficiency; calculating the expected number of vehicles to increase at the target time according to the preset time interval, the expected number of sampling vehicles and the round-trip time in transit.

[0025] Specifically, the target sampling efficiency refers to the time required for the target sampler to complete a sampling. The target sampling efficiency can be determined based on the historical sampling data of the target sampler. The round-trip time of the coal transport vehicle refers to the average time required for the coal transport vehicle to travel from the departure point to the current sampling channel and back to the departure point. This time can be calculated based on the historical transportation data corresponding to the coal transport vehicle. The preset time interval is the time interval between the target time and the current time. The preset time interval is set by the user according to actual needs. The user includes the laboratory personnel or other staff in the sampling process. The system can automatically adjust the sampling ratio of the target coal type according to the preset time interval. The target sampler is a sampler used to sample the target coal type. The expected number of sampling vehicles is the number of vehicles that the target sampler is expected to complete sampling within the preset time interval, which can also be understood as the number of vehicles that leave the sampling channel within the preset time interval.

[0026] Based on this, since there are not only returning vehicles within the preset time interval, but also vehicles that leave after sampling is completed, in order to accurately calculate the expected increase in the number of vehicles at the target time, it is necessary to first determine the expected number of sampling vehicles of the target sampler within the preset time interval, and then calculate the expected increase in the number of vehicles at the target time based on the preset time interval and the round-trip time in transit.

[0027] For example, for the target coal type A, the target coal type corresponds to only one sampling channel A, and the sampling channel is provided with a target sampler A to sample the coal transport vehicles transporting the target coal type A. The number of target vehicles is set by the supplier of the target coal type A before the start of a sampling cycle. The preset time interval set by the laboratory personnel is obtained as 2 hours, the current time is 8:00 am, and the target time is 10:00 am. The historical transportation data of coal transport vehicles in the three months before 8:00 am is obtained, and the average historical round-trip time of coal transport vehicles is 0.2 hours / vehicle. Therefore, the round-trip time of coal transport vehicles is determined to be 0.2 hours / vehicle. The historical sampling efficiency of the target sampler in the week before 8:00 am is 0.3 hours / vehicle. Therefore, the target sampling frequency of the target sampler is determined to be 0.3 hours / vehicle. According to the preset time interval and the target sampling efficiency, the expected number of sampling vehicles of the target sampler in the preset time interval is calculated to be 20. Further, the expected additional number of vehicles in the target time is calculated according to the preset time interval, the expected number of sampling vehicles and the round-trip time.

[0028] It should be noted that the historical time period corresponding to the historical sampling information is the time period from a certain historical time to the current time. The historical time period can be set by the user according to needs. The current sampling ratio needs to be adjusted every preset time interval. Therefore, the current time point corresponding to each acquisition of historical sampling information is different, and thus the historical sampling information obtained each time is also different. Such historical sampling information can more accurately reflect the operating rules of the current transport vehicles and target samplers.

[0029] In summary, the process of the embodiment of this specification fully considers the dynamics of the flow of coal transport vehicles and the sampling efficiency of the target sampler, ensuring the accuracy of the prediction results.

[0030] Furthermore, since the number of vehicles added within the preset time interval is not only the number of vehicles returning during this period, but also the number of vehicles leaving after sampling during this period, in order to accurately calculate the expected increase in the number of vehicles, the expected increase in the number of vehicles at the target time is calculated based on the preset time interval, the expected number of sampled vehicles and the round-trip time in transit, including: determining the expected number of return vehicles at the target time based on the preset time interval and the round-trip time in transit; calculating the expected increase in the number of vehicles at the target time based on the expected number of sampled vehicles and the expected number of return vehicles.

[0031] Specifically, the expected number of return vehicles refers to the total number of coal transport vehicles transporting the target type of coal that are expected to return to the current sampling channel within a preset time interval or by the target time.

[0032] Based on this, according to the preset time interval and the round trip time in transit, it is possible to determine how many vehicles are expected to return to the current sampling channel within the target time, that is, the expected number of return vehicles. This expected number of return vehicles reflects the number of vehicles in transit and is an important factor in predicting future vehicle arrivals. Then, this expected number of return vehicles is combined with the number of sampling vehicles that the target sampler is expected to complete within the preset time interval (that is, the expected number of sampling vehicles), and the expected number of additional vehicles at the target time can be obtained.

[0033] Continuing with the above example, based on the preset time interval of 2 hours and the round trip time of 0.2 hours per coal transport vehicle, it can be seen that 30 coal transport vehicles are expected to return at 9:00 am. From this, minus the expected number of sampled vehicles of 20, the expected increase in vehicles at 9:00 is 10.

[0034] It should be noted that the expected increase in vehicles can be a positive number, a negative number or 0. When the expected number of return vehicles at the target time is greater than the expected number of sampling vehicles, the expected increase in the number of vehicles is a positive number, indicating that the number of coal-transporting vehicles at the target time is actually increased; if the expected number of return vehicles at the target time is less than the expected number of sampling vehicles, the expected increase in the number of vehicles is a negative number, indicating that the number of coal-transporting vehicles at the target time is actually reduced; if the expected number of return vehicles at the target time is less than the expected number of sampling vehicles, the expected increase in the number of vehicles is a negative number, indicating that the number of coal-transporting vehicles at the target time is actually unchanged.

[0035] In summary, the embodiments of this specification comprehensively consider the vehicles that have been sampled and left and the vehicles that are expected to return on the way, so as to more accurately predict the trend of future vehicle arrivals and provide more reliable data support for adjusting the sampling ratio.

[0036] Furthermore, the changes in coal transport vehicles are different in different time periods within a sampling cycle. Therefore, in order to further improve the accuracy of the prediction of the expected number of return vehicles, the expected number of return vehicles at the target time is determined based on the preset time interval and the round-trip time in transit, including: classifying the round-trip time in transit according to the time dimension to obtain the round-trip time in transit corresponding to at least two time dimensions; determining the target round-trip time in transit corresponding to the target time dimension according to the target time dimension where the target time is located; determining the expected number of return vehicles at the target time according to the preset time interval and the target round-trip time in transit.

[0037] Specifically, the time dimension refers to different time periods within a sampling cycle, and the sampling cycle refers to the period from the start to the end of the sampling work. For example, a sampling cycle can be a day, and the different time dimensions included in the sampling cycle are morning, noon, evening, etc. The time dimensions within a sampling cycle can be set by the user according to actual needs.

[0038] Based on this, the round-trip time of coal transport vehicles can be classified according to the time dimension. In this process, the historical transportation data of coal transport vehicles must be classified according to the time dimension first, and the round-trip time of coal transport vehicles in each time dimension must be counted separately. That is, the historical transportation data lines of coal transport vehicles in the historical time period are classified according to the historical sampling period, and then the historical transportation data in each historical sampling period is classified according to at least two time dimensions, and the historical transportation data of the same time dimension in each historical sampling period is counted, and the round-trip time of coal transport vehicles in this time dimension is calculated. Similarly, the corresponding round-trip time of coal transport vehicles in other time dimensions can be calculated in this way.

[0039] When it is necessary to predict the expected number of return vehicles at a certain target time, first determine the time dimension of the target time, then select the round-trip time corresponding to the time dimension, and finally calculate the expected number of return vehicles based on the preset time interval and the target round-trip time.

[0040] Using the above example, assuming that the historical sampling period in the past three months is one day, the time dimensions are: 6:00-14:00 in the morning, 14:00-22:00 in the afternoon, and 22:00-6:00 in the evening, the historical transportation data corresponding to the three time dimensions of morning, noon, and evening are determined for each day based on the historical transportation data of the past three months, and the round-trip time of the transportation vehicles in each time dimension is calculated based on the historical data corresponding to the same time dimension every day: 0.2 hours / vehicle in the morning, 0.3 hours / vehicle in the afternoon, and 0.6 hours / vehicle in the evening. The target time is 9:00, and the time dimension is the morning dimension, and the corresponding round-trip time of the transportation vehicles in the morning is 0.2 hours / vehicle.

[0041] In summary, the embodiments of this specification take into account the differences in vehicle flows in different time periods, which can further improve the accuracy of prediction. At the same time, it is also convenient to perform statistics and analysis on historical data, providing more reliable data support for subsequent sampling ratio adjustment.

[0042] Step 106: Determine the congestion state of the current sampling channel at the target time according to the number of waiting vehicles in the current sampling channel and the estimated number of additional vehicles.

[0043] Specifically, the sampling channel refers to a channel used to sample the target coal type and for vehicles to queue or travel. The number of vehicles waiting for sampling refers to the number of vehicles that have entered the sampling channel to trigger sampling but have not yet completed sampling. The number of vehicles waiting for sampling can be directly obtained by counting the number of vehicles in the current sampling channel, or it can be determined by counting the difference between the total number of vehicles that trigger sampling at the current time and the total number of vehicles that have completed sampling.

[0044] Based on this, a comprehensive analysis is conducted based on the number of vehicles waiting for sampling in the current sampling channel and the expected number of additional vehicles to determine whether congestion will occur in the sampling channel at the target time.

[0045] Furthermore, traffic jam is an important factor affecting the sampling ratio. In the case of vehicle congestion, the vehicle transportation efficiency will be low. At this time, it is necessary to reduce the sampling of vehicles in the sampling channel while ensuring that the minimum standard samples can be obtained, thereby avoiding vehicle congestion in the sampling channel.

[0046] In order to avoid congestion in the sampling channel, it is necessary to predict the congestion in the sampling channel in advance based on the expected increase in the number of vehicles. The congestion state of the current sampling channel at the target time is determined based on the number of vehicles waiting to be sampled in the current sampling channel and the expected increase in the number of vehicles, including: obtaining the number of vehicles waiting to be sampled in the current sampling channel; calculating the expected number of vehicles waiting to be sampled in the current sampling channel at the target time based on the number of vehicles waiting to be sampled and the expected increase in the number of vehicles; judging the quantitative relationship between the expected number of vehicles waiting to be sampled and a preset vehicle number threshold, and determining the congestion state of the current sampling channel at the target time based on the quantitative relationship.

[0047] Specifically, the estimated number of waiting vehicles refers to the number of vehicles that enter the sampling channel at the target time to trigger sampling but have not yet completed sampling. The preset vehicle number threshold refers to the maximum number of vehicles that can be accommodated in the current sampling channel. The preset vehicle number threshold may change due to the influence of government and environmental protection inspections, so it can also be set by the user according to actual conditions.

[0048] Based on this, the number of waiting cars in the current sampling channel is obtained, and the number of waiting cars in the current sampling channel is added to the expected number of cars to obtain the expected number of waiting cars at the target time. The expected number of waiting cars is compared with the preset number of cars threshold. If the expected number of waiting cars is greater than the preset number of cars threshold, it is determined that the current sampling channel will be congested at the target time; if the expected number of waiting cars is less than or equal to the preset number of cars threshold, it is determined that the current sampling channel will not be congested at the target time.

[0049] For example, for the target coal type A, the number of vehicles waiting for mining in the current sampling channel A is 15, and the estimated number of additional vehicles predicted according to step 104 is 10, so the estimated number of vehicles waiting for mining is 25. The preset vehicle number threshold is 20, and since the estimated number of vehicles waiting for mining of 25 is greater than the preset vehicle number threshold of 20, it is determined that the current sampling channel A will be congested at the target time.

[0050] In summary, the embodiments of this specification can accurately predict the congestion state of the future sampling channel by comprehensively considering historical sampling information, the expected increase in the number of vehicles, and the number of vehicles waiting for sampling in the current sampling channel, providing strong data support for the adjustment of the sampling ratio, thereby ensuring the smooth progress of the sampling work.

[0051] Step 108: When the congestion state is congested, the current sampling ratio is adjusted based on the number of waiting vehicles, the expected number of additional vehicles and the reference ratio information to determine the target sampling ratio, wherein the target sampling ratio is used to sample coal transport vehicles.

[0052] Specifically, the sampling ratio refers to the ratio of the number of vehicles that need to be sampled within a sampling cycle to the total number of vehicles in this cycle. The current sampling ratio refers to the sampling ratio at the current time. The current sampling ratio is generally the highest sampling ratio. The target sampling ratio refers to the sampling ratio obtained after adjusting the current sampling ratio. After generating the target sampling ratio, the system will instruct the target sampler to sample coal transport vehicles at the target time according to the target sampling ratio.

[0053] Based on this, when the sampling channel is congested, the current sampling ratio needs to be adjusted to avoid further congestion and ensure the efficiency of the sampling work. In order to ensure that the target sampling ratio can both ensure that enough samples are obtained and avoid congestion in the sampling channel, it is necessary to comprehensively consider the number of waiting vehicles, the expected number of additional vehicles and the reference ratio information to adjust the current sampling ratio.

[0054] It should be noted that after the current sampling ratio is adjusted to obtain the target sampling ratio, the target time will be sampled according to the target sampling ratio. However, when predicting the target sampling ratio of the next target time based on the target time, the highest sampling ratio will still be adjusted as the current sampling ratio, that is, each adjustment of the sampling ratio is made based on the highest sampling ratio.

[0055] In another embodiment of the present specification, the target sampling ratio obtained after each adjustment may be used as the current sampling ratio for the next adjustment, that is, each adjustment of the sampling ratio is a further adjustment based on the previous adjustment.

[0056] Furthermore, when a traffic jam is predicted at the target time, the subsequent sampling strategy needs to be adjusted according to the traffic jam. If it is predicted that there will be no traffic jam at the target time, the current sampling ratio does not need to be adjusted. If it is predicted that there will be a traffic jam at the target time, the current sampling ratio needs to be adjusted according to the specific situation of the traffic jam. The following content will describe in detail the first method for determining the target sampling ratio provided in one embodiment of this specification.

[0057] In order to avoid or alleviate traffic jams at the target time and ensure that the samples collected can meet the standards that reflect the actual quality of the coal, the current sampling ratio is adjusted based on the number of vehicles waiting for mining, the expected increase in the number of vehicles and the reference ratio information to determine the target sampling ratio, including: determining a floating sampling ratio based on the reference ratio information, wherein the floating sampling ratio refers to the adjustable range of the current sampling ratio; calculating the ratio of vehicle number change based on the number of vehicles waiting for mining, the expected increase in the number of vehicles and a preset vehicle number threshold; adjusting the current sampling ratio based on the floating sampling ratio and the vehicle number change ratio to obtain the target sampling ratio.

[0058] Specifically, the reference sampling ratio includes the highest sampling ratio and the lowest sampling ratio, which are preset by the user. The highest sampling ratio refers to the maximum ratio of vehicles that can be sampled in a sampling cycle to the total number of vehicles, and the lowest sampling ratio refers to the minimum ratio of vehicles that must be sampled in a sampling cycle to the total number of vehicles. The floating sampling ratio refers to the maximum range within which the current sampling ratio can be adjusted, and the vehicle number change ratio is used to reflect the change of vehicles in the sampling channel at the target time.

[0059] Based on this, the floating sampling ratio can be calculated according to the highest sampling ratio and the lowest sampling ratio, and the change ratio of coal transport vehicles within the preset time period can be calculated according to the number of waiting vehicles, the expected increase in the number of vehicles and the preset vehicle number threshold. Furthermore, the actual adjustment range of the current sampling ratio is determined according to the floating sampling ratio and the vehicle number change ratio, and then the current sampling ratio is adjusted according to the adjustment range to obtain the target sampling ratio.

[0060] Using the above example, for the target coal type A, the current sampling ratio is the highest sampling ratio of 100%, the floating sampling ratio calculated based on the difference between the highest sampling ratio and the lowest sampling ratio of 60% is 40%, and the vehicle number change ratio calculated based on the current number of waiting vehicles in sampling channel A of 15, the expected increase of 10 vehicles, and the preset vehicle number threshold of 20 is 0.25. Therefore, the product of the floating sampling ratio and the vehicle number change ratio is calculated to obtain an adjustment range of 0.1 (i.e. 40%*0.25) for the current sampling ratio, which is adjusted down by 10% on the basis of the highest sampling ratio, and the target sampling ratio is 90%.

[0061] This means that when it is predicted that sampling channel A will be congested, the sampling ratio needs to be reduced from 100% to 90% to avoid further congestion and ensure the efficiency and quality of sampling.

[0062] It should be noted that if the target sampling ratio is lower than the minimum sampling ratio after adjustment, in order to ensure that there are enough samples, the target sampling ratio needs to be determined as the minimum sampling ratio.

[0063] In summary, the embodiments of this specification can accurately predict the congestion state of the future sampling channel by comprehensively considering historical sampling information, the expected increase in the number of vehicles, the number of vehicles waiting for sampling in the current sampling channel, and reference ratio information, and dynamically adjust the sampling ratio based on the prediction results, thereby ensuring the smooth progress of the sampling work and ensuring that the samples obtained can truly reflect the quality of the coal.

[0064] Furthermore, in order to accurately calculate the proportion of changes in the number of vehicles, the proportion of changes in the number of vehicles is calculated based on the number of vehicles waiting for harvest, the expected increase in the number of vehicles and a preset threshold value for the number of vehicles, including: calculating the change in the number of vehicles based on the number of vehicles waiting for harvest and the expected increase in the number of vehicles; calculating the proportion of changes in the number of vehicles based on the change in the number of vehicles and the preset threshold value for the number of vehicles.

[0065] Specifically, the change in the number of vehicles refers to the change in the number of vehicles in the current time sampling channel relative to the target time sampling channel.

[0066] Based on this, the number of waiting vehicles in the current sampling channel is subtracted from the expected number of vehicles to obtain the change in the number of vehicles. The change in the number of vehicles is then compared with the preset vehicle threshold to obtain the vehicle change ratio. The vehicle change ratio can reflect the relative change in the number of vehicles in the sampling channel at the target time, thereby providing a basis for adjusting the sampling ratio.

[0067] For example, for the target coal type A, the number of vehicles waiting for mining in sampling channel A is currently 15, and the expected number of vehicles to increase is 10. Therefore, the change in the number of vehicles is 5 (15-10). The preset vehicle number threshold is 20, so the vehicle number change ratio is 0.25 (5 / 20). This means that relative to the preset vehicle number threshold, the number of vehicles in sampling channel A at the target time will increase by 25%. Therefore, the sampling ratio needs to be appropriately reduced to avoid congestion.

[0068] In summary, by accurately calculating the change ratio of the number of vehicles, the change of the number of vehicles in the sampling channel can be more accurately predicted, so as to more reasonably adjust the sampling ratio, ensure the smooth progress of the sampling work, and improve the sampling efficiency and quality.

[0069] Furthermore, if multiple sampling channels sample the target coal type at the same time, the overall sampling ratio of each sampling channel needs to be adjusted. Therefore, another method for calculating the target sampling ratio is provided in another embodiment of the present specification. The second method for determining the target sampling ratio provided in another embodiment of the present specification will be described in detail below.

[0070] The reference ratio information includes the highest sampling ratio, the lowest sampling ratio and the standard number of sampling vehicles; based on the number of vehicles to be sampled, the expected number of additional vehicles and the reference ratio information, the current sampling ratio is adjusted to determine the target sampling ratio, including: counting the number of vehicles that have completed sampling, and determining whether the number of vehicles that have completed sampling is greater than the standard number of vehicles for sampling; if so, determining the target sampling ratio based on the lowest sampling ratio; if not, determining the target sampling ratio based on the highest sampling ratio.

[0071] Specifically, the standard number of sampling vehicles refers to a preset benchmark number of sampling vehicles in the sampling work, which is used to determine whether the current sampling progress meets the basic sampling requirements. The standard number of sampling vehicles can be set by the user according to the specific requirements of the sampling work to ensure the representativeness and accuracy of the sampling results, or it can be determined by the product of the minimum sampling ratio and the total planned number of vehicles in the sampling cycle. The planned number of vehicles refers to the number of vehicles that the supplier plans to send in the sampling cycle. It should be noted that the planned number of vehicles can be determined before the start of each sampling cycle.

[0072] Based on this, when the number of completed sampling vehicles obtained by statistics is greater than the standard number of sampling vehicles, it means that the current sampling work has been carried out to a certain extent and a sufficient number of samples have been obtained. At this time, in order to avoid congestion in the sampling channel and take into account the sampling efficiency, the target sampling ratio can be determined based on the minimum sampling ratio. This can ensure the quality of the samples while minimizing the impact on the vehicles in the sampling channel and ensuring the smooth progress of the sampling work.

[0073] On the contrary, if the number of completed sampling vehicles is less than or equal to the standard number of sampling vehicles, it means that the current sampling progress has not yet reached the preset requirements and more samples need to be collected. At this time, in order to ensure that a sufficient number of samples can be obtained to reflect the true quality of the coal, the target sampling ratio can be determined based on the highest sampling ratio. This can maximize the representativeness and accuracy of the sampling results.

[0074] For example, for the target coal type B, the preset standard number of sampling vehicles is 60. After the sampling work was carried out for a period of time at 12 noon, the number of completed sampling vehicles was statistically 40, which is less than the standard number of sampling vehicles. Therefore, at this time, the target sampling ratio should be determined based on the highest sampling ratio to ensure that a sufficient number of samples can be collected. If the number of completed sampling vehicles has reached 65, which exceeds the standard number of sampling vehicles, then the low sampling ratio of 60% can be directly used as the target sampling ratio to optimize sampling efficiency and avoid congestion.

[0075] In summary, by comprehensively considering the relationship between the number of completed sampling vehicles and the number of standard sampling vehicles, the sampling ratio can be adjusted more flexibly to ensure that the sampling work can meet the basic sampling needs while taking into account the sampling efficiency and channel congestion. This method provides strong support for the optimization of sampling work and helps to improve the overall effect and quality of sampling work.

[0076] Furthermore, in order to further improve the accuracy of the sampling ratio adjustment, the target sampling ratio is determined based on the highest sampling ratio, including: determining whether the number of completed sampling vehicles reaches the target ratio of the standard sampling number of vehicles: if so, determining the target sampling ratio based on the highest sampling ratio and a first preset adjustment ratio; if not, determining the target sampling ratio based on the highest sampling ratio and a second preset adjustment ratio, wherein the first preset adjustment ratio is less than the second preset adjustment ratio.

[0077] Specifically, the target ratio is an indicator used to measure the degree to which the number of completed sampling vehicles is relative to the standard number of sampling vehicles. The target ratio can be set according to the specific requirements of the sampling work and the actual situation. The first preset adjustment ratio and the second preset adjustment ratio are used to represent the adjustment amplitude of the maximum sampling ratio. It should be noted that in one embodiment of the present specification, in the absence of traffic jams, sampling is performed according to the highest sampling ratio by default. In this case, each sampling ratio adjustment is also made at the highest sampling ratio.

[0078] Based on this, when the number of completed sampling vehicles reaches or exceeds the target ratio of the standard sampling vehicles, it means that the current sampling work is close to the preset sampling progress requirements. At this time, in order to avoid congestion in the sampling channel and take into account the sampling efficiency, the target sampling ratio can be determined based on the highest sampling ratio and the smaller first preset adjustment ratio. This can minimize the impact on vehicles in the sampling channel while ensuring the quality of the sample and ensure the smooth progress of the sampling work.

[0079] On the contrary, if the number of completed sampling vehicles has not reached the target ratio of the standard sampling vehicles, it means that the current sampling progress still has a lot of room for improvement, and more samples need to be collected. At this time, in order to ensure that a sufficient number of samples can be obtained to more accurately reflect the true quality of the coal, the target sampling ratio can be determined based on the highest sampling ratio and the larger second preset adjustment ratio. This can maximize the representativeness and accuracy of the sampling results.

[0080] For example, for the target coal type B, the preset standard number of sampling vehicles is 60, the target ratio is 50%, the first preset adjustment ratio is 25%, and the second preset adjustment ratio is 50%. After the sampling work has been going on for a period of time and it is 12 noon, it is statistically found that the number of completed sampling vehicles is 40, and the standard number of sampling vehicles is 60, reaching 66% of the target ratio of the standard sampling vehicles (40 vehicles / 60 vehicles*100%). At this time, the target sampling ratio can be determined based on the highest sampling ratio of 100% and the smaller first preset adjustment ratio of 25%, that is, the target sampling ratio is 25% (25%*100%). Assuming that the minimum sampling ratio corresponding to the target coal type B is 40%, the currently calculated target sampling ratio is less than the minimum sampling ratio, and it cannot be guaranteed that the sample can accurately reflect the quality of the coal. Therefore, the target sampling ratio needs to be set to the minimum sampling ratio of 40%. If the number of vehicles that have completed sampling is only 25, which does not reach the target proportion of the standard sampling number of vehicles, then the target sampling ratio can be determined based on the highest sampling ratio of 100% and the larger second preset adjustment ratio of 50%, that is, the target sampling ratio is 50% (50%*100%).

[0081] In summary, by comprehensively considering the relationship between the target ratio of the number of completed sampling vehicles and the number of standard sampling vehicles, the sampling ratio can be adjusted more accurately to ensure that the sampling work can meet the basic sampling needs while taking into account the sampling efficiency and channel congestion. This method further improves the accuracy of the sampling ratio adjustment and provides strong support for the optimization of sampling work.

[0082] Furthermore, in order to prevent suppliers from cheating, providing high-quality coal first in a sampling cycle and maliciously providing low-quality coal later, it is necessary to count the quantitative relationship between the number of completed sampling vehicles and the number of standard sampling vehicles when the sampling reaches the preset progress, so as to adjust the current sampling ratio according to the implementation method of the aforementioned embodiment. Among them, the preset progress can be understood as the length of time that a sampling cycle has been carried out, and the preset progress can be represented by a time point or a time period. For example, if the sampling cycle is one day (00:01-24:00), then the preset progress can be set to 12:00, and one or more preset progresses can be set.

[0083] It should be noted that, since the returning vehicles will definitely return to this sampling channel when sampling is carried out through one sampling channel, the vehicle change ratio in the sampling channel can be determined based on the number of vehicles returning in the current sampling channel. Therefore, the first target sampling ratio determination method is preferably adopted; if there are multiple sampling channels, it is impossible to predict which sampling channel the returning vehicles will enter, and the sampling ratio needs to be adjusted according to the overall completion of the sampling. Therefore, the second sampling ratio determination method is preferred.

[0084] In summary, the embodiments of this specification set a preset schedule and adjust the sampling ratio under the schedule, making the sampling work more orderly and controllable, providing a strong guarantee for the accurate assessment of coal quality. While ensuring the sampling efficiency, it also effectively prevents possible cheating by suppliers, further improving the representativeness and accuracy of the sampling results.

[0085] Furthermore, the sampling machine in the shipping station cannot work 24 hours a day. Therefore, there is an upper limit on the number of vehicles that the sampling machine can sample every day. This upper limit is called the sampling limit. In order to avoid equipment failure or damage caused by excessive use of the sampling machine, it is necessary to strictly control the number of vehicles sampled in each sampling cycle to ensure that it does not exceed the sampling limit. When the sampling work is close to the sampling limit, the sampling ratio should be adjusted in time to reduce the pressure on the sampling machine and ensure the normal operation of the equipment.

[0086] Therefore, in another embodiment of the present specification, the current sampling ratio can also be adjusted according to the sampling limit of the target sampler, and the specific steps are as follows: Determine the target sampling efficiency of the target sampling machine contained in the historical sampling information, and obtain the preset working time of the target sampling machine; calculate the target sampling limit of the target coal type corresponding to the target sampling machine according to the preset working time and the target sampling efficiency; count the number of completed sampling vehicles, and determine whether the number of completed sampling vehicles is greater than or equal to the sampling limit. If so, determine the target sampling ratio based on the minimum sampling ratio; if not, determine the target sampling ratio based on the maximum sampling ratio.

[0087] Specifically, the preset working time is the total working time of the sampler in a sampling cycle. The preset working time can be set by the user according to work experience. The target coal type is sampled by the corresponding target sampler, and a target sampler may also need to sample multiple coal types. The target coal type is one of the multiple coal types sampled by the target sampler. Since the sampling ratios corresponding to different coal types are different, the sampling limits of the target sampler for the various coal types it needs to sample are also different. The target sampling limit refers to the maximum number of sampling vehicles for the target coal type by the target sampler in a sampling cycle.

[0088] Based on this, it is determined whether the number of vehicles that have completed sampling has reached the target sampling limit of the target sampler, so as to adjust the sampling ratio accordingly. In the case where the number of vehicles that have completed sampling has not reached the target sampling limit of the target sampler, it is further determined whether the number of vehicles that have completed sampling has reached the first target ratio of the target sampling limit. If so, the target sampling ratio is determined based on the highest sampling ratio and the third preset adjustment ratio; if not, it is determined whether the number of vehicles that have completed sampling has reached the second target ratio of the target sampling limit. If so, the target sampling ratio is determined based on the highest sampling ratio and the fourth preset adjustment ratio. If not, the target sampling ratio is determined according to the first determination method of the target sampling ratio in the aforementioned embodiment, wherein the first target ratio is greater than the second target ratio, and the third preset adjustment ratio is less than the fourth preset adjustment ratio.

[0089] Furthermore, the target sampling limit of the target coal type corresponding to the target sampling machine is calculated according to the preset working time and the target sampling efficiency, including: calculating the total sampling limit of the target sampling machine according to the preset working time and the target sampling efficiency; determining the preset sampling coal type assigned to the target sampling machine, the preset sampling coal type including the target coal type; determining the total number of coal trucks of the preset sampling coal type, and the target number of coal trucks of the target coal type, calculating the target vehicle ratio of the target number of coal trucks to the total number of coal trucks, and calculating the target sampling limit according to the target vehicle ratio and the total sampling limit.

[0090] Specifically, the preset sampling coal type refers to the coal type that needs to be sampled and is pre-assigned to the target sampling machine. The preset sampling coal type can be one or more types. Different types of coal will be pre-assigned different numbers of coal trucks for transportation. The total number of coal trucks is the total number of trucks obtained by adding the pre-assigned coal trucks corresponding to all preset sampling coal types assigned to the target sampling machine.

[0091] For example, the user sets the preset working time of the target sampler to 20 hours, and the working efficiency of the target sampler is 0.1 hours / vehicle. The total sampling limit of the target sampler is calculated to be 200 (20 / 0.1) vehicles. The preset sampling coal types corresponding to the sampling of the target sampler include coal type A, coal type B, and coal type C, among which coal type A is the target sampling coal type. The transportation vehicles corresponding to each coal type are: coal type A: 20 vehicles, coal type B: 10 vehicles, coal type C: 50 vehicles, and the corresponding target coal type's target sampling limit for the target sampler is: 50 (200*(20 / (20+10+50))). If the calculation result is a decimal, the decimal place is directly discarded and rounded down.

[0092] The number of vehicles that have completed sampling of the target coal type is 15, 15<(50 / 2), and the target sampling ratio is determined according to the first method for determining the target sampling ratio in the aforementioned embodiment.

[0093] In addition, if the number of vehicles that have completed sampling is greater than or equal to the target sampling limit, the lowest sampling ratio is used as the target sampling ratio. Assuming that the first target ratio is 3 / 4, the second target ratio is 1 / 2, the third preset adjustment ratio is 1 / 4, and the third preset adjustment ratio is 3 / 4, if the number of vehicles that have completed sampling is greater than or equal to the target sampling limit*3 / 4, the highest sampling ratio*1 / 4 is used as the target sampling ratio; if the number of vehicles that have completed sampling is greater than or equal to the target sampling limit*1 / 2, the highest sampling ratio*3 / 4 is used as the target sampling ratio.

[0094] In summary, the embodiments of this specification comprehensively consider the sampling limit of the sampler and flexibly adjust the sampling ratio to meet the needs of different sampling stages. The target sampling limit is determined by calculating the total sampling limit of the target sampler and according to the proportion of the target number of coal trucks in the total number of coal trucks. On this basis, different strategies are used to determine the target sampling ratio according to the relationship between the number of completed sampling vehicles and the target sampling limit. It ensures that the samples obtained by the final sampling meet the standards, while avoiding damage to the sampler due to excessive use, and can also avoid or alleviate traffic jams, thereby improving the overall efficiency and reliability of the sampling work.

[0095] The following combination Figure 2A and Figure 2B Taking the application of the vehicle sampling method provided in this specification in the coal transportation scenario as an example, the vehicle sampling method is further explained. Figure 2A This is a first processing flow chart of a vehicle sampling method in a coal transportation yard provided by an embodiment of this specification, steps 202 to 216; Figure 2B This is a first processing flow chart of a vehicle sampling method in a coal transportation yard provided by an embodiment of this specification, steps 208 to 236, which specifically include the following steps.

[0096] Step 202: Acquire historical sampling information and reference ratio information corresponding to the target coal type, wherein the historical sampling information includes the target sampling efficiency of the target sampler and the round-trip time of the coal transport vehicle.

[0097] Step 204: Calculate the expected number of sampling vehicles of the target sampling machine within the preset time interval according to the preset time interval and the target sampling efficiency.

[0098] Step 206: Classify the round-trip duration in transit according to the time dimension to obtain the round-trip duration in transit corresponding to at least two time dimensions.

[0099] Step 208: According to the target time dimension where the target time is located, determine the target round-trip duration corresponding to the target time dimension.

[0100] Step 210: Determine the number of vehicles expected to return within the target time based on the preset time interval and the target round-trip duration in transit.

[0101] Step 212: Calculate the expected number of additional vehicles within the target time based on the expected number of sampled vehicles and the expected number of returned vehicles.

[0102] Step 214: Obtain the number of vehicles waiting for sampling in the current sampling channel.

[0103] Step 216: Calculate the expected number of waiting vehicles for the current sampling channel at the target time based on the number of waiting vehicles and the expected number of additional vehicles.

[0104] Step 218: Determine the quantitative relationship between the estimated number of waiting vehicles and a preset vehicle number threshold, and determine the congestion state of the current sampling channel at the target time based on the quantitative relationship.

[0105] Step 220: Determine a floating sampling ratio according to the reference ratio information, wherein the floating sampling ratio refers to an adjustable range of the current sampling ratio.

[0106] Step 222: Calculate the change in the number of vehicles based on the number of vehicles waiting for collection and the expected number of additional vehicles.

[0107] Step 224: Calculate the vehicle number change ratio according to the vehicle number change amount and the preset vehicle number threshold.

[0108] Step 226: According to the floating sampling ratio and the vehicle number change ratio, the current sampling ratio is adjusted to obtain a target sampling ratio.

[0109] Step 228: The reference ratio information includes the highest sampling ratio, the lowest sampling ratio and the standard number of sampling vehicles. The number of vehicles that have completed sampling is counted to determine whether the number of vehicles that have completed sampling is greater than the standard number of sampling vehicles. If so, execute step 230; if not, execute step 232.

[0110] Step 230: Determine the target sampling ratio based on the minimum sampling ratio.

[0111] Step 232: Determine whether the number of vehicles that have completed sampling has reached the target ratio of the standard number of vehicles for sampling: if so, execute step 234; if not, execute step 236.

[0112] Step 234: Determine the target sampling ratio based on the highest sampling ratio and the first preset adjustment ratio.

[0113] Step 236: determining the target sampling ratio based on the highest sampling ratio and a second preset adjustment ratio, wherein the first preset adjustment ratio is smaller than the second preset adjustment ratio.

[0114] In summary, the embodiments of this specification can dynamically adjust the sampling ratio through accurate calculation of the number of waiting vehicles, the expected increase in the number of vehicles, and the ratio of the change in the number of vehicles, so as to adapt to the sampling needs in different situations. Combining historical sampling information and reference ratio information, it is possible to intelligently predict future congestion and make reasonable sampling plans accordingly. At the same time, considering the relationship between the number of completed sampling vehicles and the standard number of sampling vehicles, the controllability and anti-cheating ability of the sampling work are further enhanced. The embodiments of this specification realize the intelligent, efficient and accurate sampling work by comprehensively considering various factors and taking corresponding adjustment measures. This not only improves the reliability of coal quality assessment, but also improves the flexibility and accuracy of sampling work.

[0115] The following combination Figure 3A and Figure 3B Taking the application of the vehicle sampling method provided in this specification in the coal transportation scenario as an example, another implementation method of the vehicle sampling method is further described. Figure 3A It is a second processing flow chart of a vehicle sampling method in a coal transportation yard provided by an embodiment of this specification, steps 302 to 330; Figure 3B This is a second processing flow chart of a vehicle sampling method in a coal transportation yard provided by an embodiment of the present specification, steps 332 to 368, which specifically include the following steps.

[0116] Step 302: Find the coal suppliers corresponding to all sampling machines.

[0117] For all the sampling machines in the entire shipping station, the types of coal sampled by each sampling machine may be different, and the suppliers corresponding to different types of coal may also be different. Therefore, in order to accurately adjust the sampling ratios corresponding to different types of coal, it is necessary to first determine the correspondence between the sampling machines, coal types, and suppliers.

[0118] Step 304: Obtain the factory, supplier, type of coal, number of corresponding sampling channels, total number of vehicles that can return on the day, and total number of current samples.

[0119] Step 306: Obtain the number of coal trucks in the sampling channel corresponding to each current sampling machine.

[0120] For any target coal type, determine the sampling machine used to sample the target coal type, and determine the number of vehicles in the sampling channel corresponding to each current sampling machine.

[0121] Step 308: Obtain the estimated sampling number of the sampler at the next moment.

[0122] The estimated sampling number of the sampling machine at the next moment has the same meaning as the estimated number of sampling vehicles described in the above embodiment.

[0123] Step 310: Obtain the total number of vehicles that can be accommodated by each sampling machine channel, the total number of vehicles dispatched by the supplier for each type of coal on that day, and the number of vehicles that can return for each type of coal at the next moment.

[0124] Since there may be multiple sampling machines for sampling the target coal type, each sampling machine corresponds to a sampling channel. The maximum number of vehicles that can be accommodated in each sampling channel, the total number of vehicles dispatched by suppliers for each coal type on that day, and the number of vehicles that can return for each coal type at the target time are obtained.

[0125] Step 312: Obtain the supplier's optimal sampling number, sampled number, and remaining sampling number of coal types.

[0126] The optimal sampling number refers to the minimum number of samples that can reflect the coal quality of a certain type of coal. The number of samples already collected refers to the number of coal transport vehicles that have completed sampling for a certain type of coal. The remaining number of samples refers to the number of vehicles that need to continue sampling to ensure that the optimal sampling number is met.

[0127] Step 314: Determine whether the sampling machine is faulty, if so, execute step 316, if not, execute step 320.

[0128] Determine whether the sampling machine used to sample a certain type of coal has malfunctioned.

[0129] Step 316: Sampler failure: 0.

[0130] If the sampler fails, set the corresponding status code to 0.

[0131] Step 318: The sampling ratio is 0.

[0132] When the sampler fails, it means that normal sampling cannot be performed and the sampler needs to be controlled to stop working, so the sampling ratio is set to 0.

[0133] Step 320: Determine whether the supplier's coal type is cleared in the sampling machine; if so, execute step 322; if not, execute step 326.

[0134] Determine whether the sampling barrel used to hold a certain type of coal has been cleared.

[0135] Step 322: The current coal type has been cleared from the barrel: 1.

[0136] If the target coal type has been cleared, the status code is set to 1.

[0137] Step 324: The sampling ratio shall be in accordance with the audit requirements.

[0138] Step 326: Whether to enable the concentrated vehicle ratio adjustment; if so, execute step 328; if not, execute step 332.

[0139] In the case that the barrel is not cleared, it is up to the user to determine whether to enable the centralized vehicle proportion adjustment, that is, to make an overall adjustment to the sampling proportion corresponding to a certain type of coal.

[0140] Step 328: Adjust the proportion of concentrated vehicles: 8.

[0141] If overall adjustment is required, the status code is set to 8.

[0142] Step 330: Configure the corresponding return sampling ratio according to the number of vehicles that have been inspected.

[0143] The current sampling ratio is adjusted according to the number of vehicles that have completed sampling.

[0144] Step 332: Is there a traffic jam in the sampling machine channel? If so, execute step 334; if not, execute step 336.

[0145] Determine whether there will be traffic jam in the sampling channel corresponding to the target coal type at the target time.

[0146] Step 334: Traffic jam occurs: 2.

[0147] If a traffic jam occurs, the status code is set to 2.

[0148] Step 336: Afternoon supplementary sampling control: If yes, execute step 338; if not, execute step 340.

[0149] After noon, we can determine whether the current sampling ratio needs to be adjusted based on whether the number of completed sampling vehicles reaches the standard number of sampling vehicles.

[0150] Step 338: Afternoon supplementary sampling control: 7.

[0151] The need for additional sampling control means that the current sampling ratio needs to be adjusted and the status code is set to 7.

[0152] Step 340: Whether the sampling limit of the sampler has been reached.

[0153] Determine whether the number of vehicles that have completed sampling of a certain type of coal has reached the sampling limit of the sampling machine.

[0154] Step 342: Target sampling ratio = minimum sampling ratio: 3.

[0155] If the sampling limit is reached, the sampling ratio is adjusted to the minimum sampling ratio and the status code is set to 3.

[0156] Step 344: The number of sampled vehicles reaches the 3 / 4 sampling limit; if so, execute step 346; if not, execute step 348.

[0157] If the sampling limit is not reached, determine whether the number of sampled vehicles has reached 3 / 4 of the sampling limit.

[0158] Step 346: Target sampling ratio = 1 / 4 Maximum sampling ratio: 5.

[0159] If the number of sampled vehicles reaches 3 / 4 of the sampling limit, the sampling ratio will be adjusted to 1 / 4 of the maximum sampling ratio, and the status code will be set to 5.

[0160] Step 348: The number of sampled vehicles reaches 1 / 2 sampling limit; if so, execute step 350; if not, execute step 358.

[0161] Step 350: Target sampling ratio = 3 / 4 Maximum sampling ratio: 6.

[0162] If the number of sampled vehicles reaches 3 / 4 of the sampling limit, the sampling ratio is adjusted to 3 / 4 of the maximum sampling ratio, and the status code is set to 6. It should be noted that although the sampling ratio has been adjusted in step 342, step 346, and step 350, the number of completed sampling vehicles may be less than the standard sampling number of vehicles set by the user. In order to ensure that the number of sampled vehicles meets the standard, it is necessary to continue to execute step 352 after executing any one of step 342, step 346, and step 350.

[0163] Step 352: Is the number of quality inspection vehicles for the current sampled coal type sufficient? If so, execute step 354; if not, execute step 356.

[0164] When any of steps 332, 336, 340, 344, and 348 meets the conditions, the process can jump to step 352 to determine whether the number of vehicles that have completed sampling has reached the standard number of vehicles for sampling.

[0165] Step 354: Set the corresponding sampling ratio according to the status code.

[0166] If the standard number of sampling vehicles has been reached, the sampling ratio can be set according to the status code. Since different status codes represent different status conditions, the system can determine what status conditions are met in the previous step based on the status code, and then adjust the sampling ratio.

[0167] Step 356: The number of vehicles inspecting the current type of coal is too small, so every vehicle must undergo quality inspection.

[0168] If the standard number of sampling vehicles is not reached, sampling will be required for every subsequent vehicle.

[0169] Step 358: Dynamic adjustment of sampling ratio: 4.

[0170] If the number of sampled vehicles does not reach 1 / 2 of the sampling limit, the sampling ratio needs to be dynamically adjusted and the status code is set to 4.

[0171] Step 360: Is the current coal type blocked in other sampling machine channels? If so, execute step 362; if not, execute step 364.

[0172] The current coal type has the same meaning as the target coal type in the aforementioned embodiment, and the sampling machine channel has the same meaning as the sampling channel in the aforementioned embodiment.

[0173] Step 362: The supplier's coal type takes the lowest sampling ratio when there is a traffic jam at other sampling machines.

[0174] If a traffic jam occurs in the sampling channel corresponding to the target coal type at the current time, the current sampling ratio is adjusted to a low sampling ratio for sampling.

[0175] Step 364: predict whether the sampling machine channel will be congested at the next moment; if so, execute step 366; if not, execute step 368.

[0176] Predict whether the sampling channel at the target time will be congested at the target time.

[0177] Step 366: The predicted traffic jam sampling ratio at the next moment is adjusted to a maximum ratio of 3 / 4.

[0178] If a traffic jam is predicted, the sampling ratio of the target time is adjusted to 3 / 4 of the maximum sampling ratio.

[0179] Step 368: The supplier coal type fluctuates between the highest proportion and the lowest proportion.

[0180] The adjusted target sampling ratio always fluctuates between the highest sampling ratio and the lowest sampling ratio.

[0181] The embodiments of this specification realize the refined management and intelligent adjustment of the sampling ratio. By combining multiple factors, such as coal type, supplier, sampling machine status, sampling channel congestion, etc., the system can automatically determine and adjust the sampling ratio to adapt to different sampling needs and actual conditions, thereby improving sampling efficiency.

[0182] Corresponding to the above method embodiment, this specification also provides a vehicle sampling device embodiment, Figure 4 FIG. 1 shows a schematic diagram of the structure of a vehicle sampling device provided by an embodiment of this specification. Figure 4 As shown, the device comprises: The data acquisition module 402 is configured to acquire historical sampling information and reference ratio information corresponding to the target coal type; The data calculation module 404 is configured to predict the expected increase in the number of vehicles at the target time based on the historical sampling information; The state determination module 406 is configured to determine the congestion state of the current sampling channel at the target time according to the number of waiting vehicles in the current sampling channel and the expected number of additional vehicles; The sampling module 408 is configured to adjust the current sampling ratio and determine the target sampling ratio based on the number of waiting vehicles, the expected number of additional vehicles and the reference ratio information when the congestion state is congestion, wherein the target sampling ratio is used to sample coal transport vehicles.

[0183] The data calculation module 404 includes: The estimated sampling vehicle number calculation submodule is configured to calculate the estimated sampling vehicle number of the target sampling machine within the preset time interval according to the preset time interval and the target sampling efficiency; The estimated additional vehicle number calculation submodule is configured to calculate the estimated additional vehicle number at the target time according to the preset time interval, the estimated number of sampled vehicles and the round-trip time in transit.

[0184] The estimated additional vehicle number calculation submodule is further configured as follows: Determine the estimated number of return vehicles at the target time according to the preset time interval and the round trip duration in transit; The estimated number of additional vehicles within the target time is calculated based on the estimated number of sampled vehicles and the estimated number of returned vehicles.

[0185] The estimated additional vehicle number calculation submodule is further configured as follows: Classifying the round-trip duration in transit according to the time dimension to obtain the round-trip duration in transit corresponding to at least two time dimensions; According to the target time dimension where the target time is located, determine the target round-trip duration corresponding to the target time dimension; The number of vehicles expected to return within the target time is determined based on the preset time interval and the target round-trip duration in transit.

[0186] The state determination module 406 is further configured to: Get the number of waiting vehicles in the current sampling channel; Calculate the expected number of waiting vehicles for collection at the target time for the current sampling channel according to the number of waiting vehicles for collection and the expected number of additional vehicles; The quantitative relationship between the estimated number of waiting vehicles and a preset vehicle number threshold is determined, and the congestion state of the current sampling channel at the target time is determined according to the quantitative relationship.

[0187] The sampling module 408 includes: The first sampling ratio adjustment submodule is configured as follows: Determine a floating sampling ratio according to the reference ratio information, wherein the floating sampling ratio refers to an adjustable range of the current sampling ratio; Calculate the change ratio of the number of vehicles according to the number of waiting vehicles, the expected number of additional vehicles and the preset vehicle number threshold; According to the floating sampling ratio and the vehicle number change ratio, the current sampling ratio is adjusted to obtain a target sampling ratio.

[0188] The first sampling ratio adjustment submodule is further configured as follows: Calculate the change in the number of vehicles according to the number of waiting vehicles and the expected number of additional vehicles; The vehicle number change ratio is calculated according to the vehicle number change amount and a preset vehicle number threshold.

[0189] The reference ratio information includes the highest sampling ratio, the lowest sampling ratio and the number of standard sampling vehicles; The sampling module 408 includes: The second sampling ratio adjustment submodule is configured as follows: Counting the number of vehicles that have completed sampling, and determining whether the number of vehicles that have completed sampling is greater than the standard number of vehicles for sampling; If so, determining the target sampling ratio based on the minimum sampling ratio; If not, the target sampling ratio is determined based on the highest sampling ratio.

[0190] The second sampling ratio adjustment submodule is further configured as follows: Determine whether the number of completed sampling vehicles reaches the target ratio of the standard sampling vehicles: If yes, determining the target sampling ratio based on the highest sampling ratio and the first preset adjustment ratio; If not, the target sampling ratio is determined based on the highest sampling ratio and a second preset adjustment ratio, wherein the first preset adjustment ratio is smaller than the second preset adjustment ratio.

[0191] The above is a schematic scheme of a vehicle sampling device of this embodiment. It should be noted that the technical scheme of the vehicle sampling device and the technical scheme of the above-mentioned vehicle sampling method belong to the same concept, and the details not described in detail in the technical scheme of the vehicle sampling device can be referred to the description of the technical scheme of the above-mentioned vehicle sampling method.

[0192] Figure 5 The structure block diagram of a computing device 500 provided according to an embodiment of the present specification is shown. The components of the computing device 500 include but are not limited to a memory 510 and a processor 520. The processor 520 is connected to the memory 510 via a bus 530, and the database 550 is used to store data.

[0193] The computing device 500 also includes an access device 540 that enables the computing device 500 to communicate via one or more networks 560. Examples of these networks include a public switched telephone network (PSTN), a local area network (LAN), a wide area network (WAN), a personal area network (PAN), or a combination of communication networks such as the Internet. The access device 540 may include one or more of any type of network interface (e.g., a network interface card (NIC)) that is wired or wireless, such as an IEEE 802.11 wireless local area network (WLAN) wireless interface, a world-wide interoperability for microwave access (Wi-MAX) interface, an Ethernet interface, a universal serial bus (USB) interface, a cellular network interface, a Bluetooth interface, and a near field communication (NFC).

[0194] In one embodiment of the present specification, the above components of the computing device 500 and Figure 5 Other components not shown in the figure may also be connected to each other, for example, via a bus. It should be understood that Figure 5 The computing device structure block diagram shown is only for the purpose of illustration, and is not intended to limit the scope of this specification. Those skilled in the art can add or replace other components as needed.

[0195] The computing device 500 may be any type of stationary or mobile computing device, including a mobile computer or mobile computing device (e.g., a tablet computer, a personal digital assistant, a laptop computer, a notebook computer, a netbook, etc.), a mobile phone (e.g., a smart phone), a wearable computing device (e.g., a smart watch, smart glasses, etc.), or other types of mobile devices, or a stationary computing device such as a desktop computer or a personal computer (PC). The computing device 500 may also be a mobile or stationary server.

[0196] The processor 520 is used to execute the following computer executable instructions, which, when executed by the processor, implement the steps of the above-mentioned vehicle sampling method.

[0197] The above is a schematic scheme of a computing device of this embodiment. It should be noted that the technical scheme of the computing device and the technical scheme of the above-mentioned vehicle sampling method belong to the same concept, and the details not described in detail in the technical scheme of the computing device can be referred to the description of the technical scheme of the above-mentioned vehicle sampling method.

[0198] An embodiment of the present specification also provides a computer-readable storage medium storing computer-executable instructions, which can implement the steps of the above-mentioned vehicle sampling method when executed by a processor.

[0199] The above is a schematic scheme of a computer-readable storage medium of this embodiment. It should be noted that the technical scheme of the storage medium and the technical scheme of the above-mentioned vehicle sampling method belong to the same concept, and the details not described in detail in the technical scheme of the storage medium can be referred to the description of the technical scheme of the above-mentioned vehicle sampling method.

[0200] An embodiment of the present specification further provides a computer program, wherein when the computer program is executed in a computer, the computer is caused to execute the steps of the above-mentioned vehicle sampling method.

[0201] The above is a schematic scheme of a computer program of this embodiment. It should be noted that the technical scheme of the computer program and the technical scheme of the above-mentioned vehicle sampling method belong to the same concept, and the details not described in detail in the technical scheme of the computer program can be referred to the description of the technical scheme of the above-mentioned vehicle sampling method.

[0202] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0203] The computer instructions include computer program codes, which may be in source code form, object code form, executable files or some intermediate forms, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that the content contained in the computer-readable medium may be appropriately increased or decreased according to the requirements of patent practice. For example, in some regions, according to patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0204] It should be noted that, for the above-mentioned method embodiments, for the sake of simplicity of description, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the embodiments of this specification are not limited by the order of the actions described, because according to the embodiments of this specification, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the embodiments of this specification.

[0205] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0206] The preferred embodiments of this specification disclosed above are only used to help explain this specification. The optional embodiments do not describe all the details in detail, nor do they limit the invention to only the specific implementation methods described. Obviously, many modifications and changes can be made according to the content of the embodiments of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the embodiments of this specification, so that technicians in the relevant technical field can well understand and use this specification. This specification is only limited by the claims and their full scope and equivalents.

Claims

1. A vehicle sampling method, characterized in that: include: Obtain historical sampling information and reference ratio information corresponding to the target coal type; Based on the historical sampling information, predict the expected increase in the number of vehicles at the target time; Determine the congestion state of the current sampling channel at the target time according to the number of waiting vehicles in the current sampling channel and the expected number of additional vehicles; When the congestion state is congested, the current sampling ratio is adjusted based on the number of waiting vehicles, the expected number of additional vehicles and the reference ratio information to determine the target sampling ratio, wherein the target sampling ratio is used to sample coal transport vehicles.

2. The vehicle sampling method according to claim 1, characterized in that: The historical sampling information includes the target sampling efficiency of the target sampling machine and the round trip time of the coal transport vehicle; The predicting of the expected increase in the number of vehicles at the target time based on the historical sampling information includes: According to the preset time interval and the target sampling efficiency, calculating the expected number of sampling vehicles of the target sampling machine within the preset time interval; The estimated additional number of vehicles within the target time is calculated based on the preset time interval, the estimated number of sampled vehicles and the round-trip time in transit.

3. The vehicle sampling method according to claim 2, characterized in that: The step of calculating the estimated number of additional vehicles within the target time according to the preset time interval, the estimated number of sampled vehicles, and the round-trip time in transit includes: Determine the estimated number of return vehicles at the target time according to the preset time interval and the round trip duration in transit; The estimated number of additional vehicles within the target time is calculated based on the estimated number of sampled vehicles and the estimated number of returned vehicles.

4. The vehicle sampling method according to claim 3, characterized in that: The step of determining the estimated number of return vehicles at the target time according to the preset time interval and the round trip duration in transit includes: Classifying the round-trip duration in transit according to the time dimension to obtain the round-trip duration in transit corresponding to at least two time dimensions; According to the target time dimension where the target time is located, determine the target round-trip duration corresponding to the target time dimension; The number of vehicles expected to return within the target time is determined based on the preset time interval and the target round-trip duration in transit.

5. The vehicle sampling method according to claim 1, characterized in that: The determining, according to the number of waiting vehicles in the current sampling channel and the expected number of additional vehicles, the congestion state of the current sampling channel at the target time includes: Get the number of waiting vehicles in the current sampling channel; Calculate the expected number of waiting vehicles for collection at the target time for the current sampling channel according to the number of waiting vehicles for collection and the expected number of additional vehicles; The quantitative relationship between the estimated number of waiting vehicles and a preset vehicle number threshold is determined, and the congestion state of the current sampling channel at the target time is determined according to the quantitative relationship.

6. The vehicle sampling method according to claim 1, characterized in that: The adjusting the current sampling ratio based on the number of waiting vehicles, the expected number of additional vehicles and the reference ratio information to determine the target sampling ratio includes: Determine a floating sampling ratio according to the reference ratio information, wherein the floating sampling ratio refers to an adjustable range of the current sampling ratio; Calculate the change ratio of the number of vehicles according to the number of waiting vehicles, the expected number of additional vehicles and the preset vehicle number threshold; According to the floating sampling ratio and the vehicle number change ratio, the current sampling ratio is adjusted to obtain a target sampling ratio.

7. The vehicle sampling method according to claim 6, characterized in that: According to the waiting number of vehicles, the expected additional number of vehicles and the preset vehicle number threshold, the vehicle number change ratio is calculated, including: Calculate the change in the number of vehicles according to the number of waiting vehicles and the expected number of additional vehicles; The vehicle number change ratio is calculated according to the vehicle number change amount and a preset vehicle number threshold.

8. The vehicle sampling method according to claim 1, characterized in that: The reference ratio information includes the highest sampling ratio, the lowest sampling ratio and the number of standard sampling vehicles; The adjusting the current sampling ratio based on the number of waiting vehicles, the expected number of additional vehicles and the reference ratio information to determine the target sampling ratio includes: Counting the number of vehicles that have completed sampling, and determining whether the number of vehicles that have completed sampling is greater than the standard number of vehicles for sampling; If so, determining the target sampling ratio based on the minimum sampling ratio; If not, the target sampling ratio is determined based on the highest sampling ratio.

9. The vehicle sampling method according to claim 8, characterized in that: The determining the target sampling ratio based on the highest sampling ratio comprises: Determine whether the number of completed sampling vehicles reaches the target ratio of the standard sampling vehicles: If yes, determining the target sampling ratio based on the highest sampling ratio and the first preset adjustment ratio; If not, the target sampling ratio is determined based on the highest sampling ratio and a second preset adjustment ratio, wherein the first preset adjustment ratio is smaller than the second preset adjustment ratio.

10. A vehicle sampling device, characterized in that: include: A data acquisition module is configured to acquire historical sampling information and reference ratio information corresponding to the target coal type; A data calculation module is configured to predict the expected increase in the number of vehicles at the target time based on the historical sampling information; A state judgment module is configured to determine the congestion state of the current sampling channel at the target time according to the number of waiting vehicles in the current sampling channel and the expected number of additional vehicles; The sampling module is configured to adjust the current sampling ratio and determine the target sampling ratio based on the number of waiting vehicles, the expected number of additional vehicles and the reference ratio information when the congestion state is congested, wherein the target sampling ratio is used to sample coal transport vehicles.

11. A computing device, characterized in that: include: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of the vehicle sampling method according to any one of claims 1 to 9 are implemented.

12. A computer-readable storage medium, characterized in that: It stores computer executable instructions, which, when executed by a processor, implement the steps of the vehicle sampling method described in any one of claims 1 to 9.

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