Fire coal allocation and transportation full-period visualization method and system
Through the visual monitoring and early warning system for the entire cycle of coal-fired transportation, the problem of lack of effective monitoring in coal-fired transportation is solved, and dynamic adjustment and transportation planning is realized, reducing costs and improving management efficiency.
Patent Information
- Application Number
- CN202510611495.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-05-13
- Publication Date
- 2025-08-15
AI Technical Summary
The lack of effective monitoring during the existing coal-fired transportation process has led to the inability to timely and dynamically correct the overall transportation plan, increasing transportation costs and economic losses.
By periodically monitoring the transport sub-path of each ship in transit, using the Gantt chart to monitor the transportation status in real time, and generating a transportation deviation value and early warning instructions to dynamically adjust the transportation plan.
It improves the monitoring efficiency of the entire cycle of coal-fired transportation, promptly warns of abnormal problems, reduces the overall transportation cost, and improves management efficiency.
Smart Images
Figure CN120494749A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the technical field of coal transportation, and in particular to a method and system for visualizing the entire cycle of coal transportation. Background Art
[0002] At present, thermal power generation is still the main mode of power generation, so the safe acquisition, transportation and management of fuel for thermal power generation becomes extremely important. Reasonable transportation methods can not only make fuel scheduling safer, but also reduce fuel scheduling costs.
[0003] However, the existing fuel transportation process lacks effective monitoring. When managers face multiple transportation orders, they are unable to effectively monitor the actual transportation parameters of each transportation order. As a result, when some transport ships are delayed, the overall transportation plan cannot be dynamically revised, resulting in high demurrage fees and increased transportation costs, causing relatively serious economic losses. Summary of the Invention
[0004] The purpose of this application is: to solve the above technical problems, this application provides a full-cycle visualization method and system for coal transportation, aiming to improve the monitoring efficiency of the full-cycle coal transportation, timely issue early warnings for abnormal transportation problems, and improve the management efficiency of coal transportation.
[0005] In some embodiments of the present application, by periodically analyzing all the transfer order parameters, a transfer sub-path is established for each ship in transit, and the transportation status of each ship is monitored in real time through a Gantt chart. The difference between the transfer plan and the actual execution status is visually compared, which is convenient for management personnel to query. At the same time, abnormal problems in the transfer process can be warned in time, thereby dynamically adjusting the overall transfer plan, reducing the overall transfer cost, and improving the management efficiency of coal transfer.
[0006] In some embodiments of the present application, a single transport sub-path is evaluated and multiple monitoring points are established to comprehensively monitor the transport sub-path. A deviation evaluation value of the transport sub-path is generated based on the real-time data of each monitoring point, and a timely warning of the delay risk of the current transport sub-path is issued, making it easier for management personnel to correct the transport plan.
[0007] In some embodiments of the present application, a method for visualizing the entire coal transportation cycle is provided, including: Set multiple transfer sub-paths based on the obtained transfer order parameters; Obtain monitoring data packets for each dispatch sub-path according to preset monitoring time nodes, and generate dispatch deviation values for each dispatch sub-path; Generate a monitoring display diagram and determine whether to generate an early warning instruction based on all transportation deviation values.
[0008] In some embodiments of the present application, when multiple dispatch sub-paths are set, the following steps are included: Traverse the transfer order parameters according to the preset update time node; Create a transfer order sequence B, B=(b1,b2…b i …b n ), where b i is the i-th transfer order; n is the number of transfer orders; According to the transfer order sequence B, set bi as the target transfer order in sequence; Obtain transaction data of the target transfer order; Generate the expected transfer trajectory of the target transfer order based on transaction data; Set up multiple monitoring points within the expected transportation trajectory; Generate the transport sub-path of the target transport order based on the expected transport trajectory and all monitoring points; Generate the transfer sub-paths for each transfer order in sequence; Establish a sequence of transport sub-paths A, A=(a1, a2…a i …a n ), where a i is the i-th transport subpath.
[0009] In some embodiments of the present application, generating the transport deviation value of each transport sub-path includes: Set a in sequence according to the transport sub-path A i Transport subpaths to the target; Obtain the monitoring data packet of the target dispatch sub-path at the current monitoring time node; Generate the real-time position of the vessel within the target transport sub-path based on the monitoring data packet; Generate the progress deviation value U of the target dispatch sub-path at the current monitoring time node based on the real-time position; Generate the remaining running path of the target dispatch sub-path at the current monitoring time node based on the real-time location; Set all monitoring points within the remaining operation path as first-level monitoring points; Establish a first-level monitoring point sequence P, P=(p1, p2…p i …p m ), where p i is the i-th first-level monitoring point in the remaining operation path; m is the number of first-level monitoring points in the remaining operation path; Generate interference evaluation values for each first-level monitoring point; Establish the interference evaluation value sequence C, C=(c1,c2…c i …c m ), where c i is the interference evaluation value of the i-th first-level monitoring point; Generate the dispatch deviation value f of the target dispatch subpath at the current monitoring time node based on the progress deviation value U and the interference evaluation value sequence C; Generate the transport deviation value of each transport sub-path at the current monitoring time node in sequence; Establish the sequence of deviation values F, F=(f1,f2…f i …f n ), where f i is the dispatch deviation value of the i-th dispatch sub-path at the current monitoring time node.
[0010] In some embodiments of the present application, generating a dispatch deviation value f of a target dispatch subpath at a current monitoring time node includes: f=e1*Q1*U+e2*Q2* (β i *c i ); Wherein, e1 is the preset first weight coefficient; e2 is the preset second weight coefficient; Q1 is the preset first fixed coefficient; Q2 is the preset second fixed coefficient; β i is the impact factor of the i-th first-level monitoring point in the remaining operation path.
[0011] In some embodiments of the present application, generating an interference evaluation value for each primary monitoring point includes: According to the first-level monitoring point sequence P, set p i It is the target first-level monitoring point; Generate the expected time point for the ship in the target transportation sub-path to arrive at the target first-level monitoring point; Generate characteristic data of the target first-level monitoring point at the expected time point based on the preset monitoring model; Generate the interference evaluation value c of the target first-level monitoring point; c=t*[ η i *Y(i)*(k i -k' i )]; Where t is the compensation coefficient generated based on the credibility of the preset monitoring model; θ is the number of interference indicators at the target first-level monitoring point; η i is the influencing factor of the i-th interference index of the target first-level monitoring point; k i is the real-time reference value of the interference index of the target first-level monitoring point generated based on the characteristic data; k' i is the standard reference value of the interference index of the target first-level monitoring point; Y(i) is the selection coefficient; if (k i -k' i )>0,Y(i)=1; if(k i -k' i)<0,Y(i)=0; Generate the interference evaluation value of each first-level monitoring point in turn.
[0012] In some embodiments of the present application, generating a monitoring display diagram includes: Create an initial display image; Set the display parameters of each transport sub-path according to the transport deviation value sequence F; Generate coal category sequence D according to historical coal burning parameters, D=(d1,d2…d i …d r ), where d i is the i-th coal category; r is the number of coal categories; Establish an association network based on the coal category sequence D and the transportation sub-path sequence A; Based on the initial display diagram, the ecological monitoring display diagram of the display parameters of the association network and each transportation sub-path is displayed.
[0013] In some embodiments of the present application, determining whether to generate a warning instruction based on all dispatch deviation values includes: Preset the first transport deviation threshold F1; Get the transport deviation value sequence F; If f i >F1, the i-th dispatch sub-path generates a first-level warning instruction at the current monitoring time node; Generate the operation risk value g based on all the transport deviation values; g=e3*Q3*[ (j i *h i )]+e4*Q4*[ (w i *f i )]; Among them, e3 is the preset third weight coefficient; e4 is the preset fourth weight coefficient; Q3 is the preset third fixed coefficient; Q4 is the preset fourth fixed coefficient; r is the number of coal categories; j i is the impact factor of the i-th coal category; h i is the risk value of coal shortage of the ith coal category generated based on all transportation deviation values; w i is the impact factor of the i-th transport sub-path; f i is the transfer deviation value of the i-th transfer sub-path at the current monitoring time node; n is the number of transfer orders; Preset operation risk value threshold G1; If g>G1, generate a secondary warning instruction.
[0014] In some embodiments of the present application, a full-cycle visualization system for coal transportation is provided, including: The central control unit sets multiple transfer sub-paths based on the obtained transfer order parameters; Monitoring unit, used to collect multi-source data; The monitoring unit is further configured to generate a monitoring data packet for each dispatch sub-path according to a preset monitoring time node; The central control unit includes: The first processing module is used to set multiple transportation sub-paths; The second processing module generates a dispatch deviation value for each dispatch sub-path according to all monitoring data packets; The early warning module is used to determine whether to generate an early warning instruction based on all the transportation deviation values; A display module, used for generating a monitoring display graph; The first processing module is further configured to: Traverse the transfer order parameters according to the preset update time node; Create a transfer order sequence B, B=(b1,b2…b i …b n ), where b i is the i-th transfer order; n is the number of transfer orders; According to the transfer order sequence B, set bi as the target transfer order in sequence; Obtain transaction data of the target transfer order; Generate the expected transfer trajectory of the target transfer order based on transaction data; Set up multiple monitoring points within the expected transportation trajectory; Generate the transport sub-path of the target transport order based on the expected transport trajectory and all monitoring points; Generate the transfer sub-paths for each transfer order in sequence; Establish a sequence of transport sub-paths A, A=(a1, a2…a i …a n ), where a i is the i-th transport subpath.
[0015] In some embodiments of the present application, the second processing module is further configured to: Set a in sequence according to the transport sub-path A i Transport subpaths to the target; Obtain the monitoring data packet of the target dispatch sub-path at the current monitoring time node; Generate the real-time position of the vessel within the target transport sub-path based on the monitoring data packet; Generate the progress deviation value U of the target dispatch sub-path at the current monitoring time node based on the real-time position; Generate the remaining running path of the target dispatch sub-path at the current monitoring time node based on the real-time location; Set all monitoring points within the remaining operation path as first-level monitoring points; Establish a first-level monitoring point sequence P, P=(p1, p2…p i …p m ), where p i is the i-th first-level monitoring point in the remaining operation path; m is the number of first-level monitoring points in the remaining operation path; Generate interference evaluation values for each first-level monitoring point; Establish the interference evaluation value sequence C, C=(c1,c2…c i …c m ), where c i is the interference evaluation value of the i-th first-level monitoring point; Generate the dispatch deviation value f of the target dispatch subpath at the current monitoring time node based on the progress deviation value U and the interference evaluation value sequence C; Generate the transport deviation value of each transport sub-path at the current monitoring time node in sequence; Establish the sequence of deviation values F, F=(f1,f2…f i …f n ), where f i is the dispatch deviation value of the i-th dispatch sub-path at the current monitoring time node.
[0016] In some embodiments of the present application, the early warning module is further configured to: Preset the first transport deviation threshold F1; Get the transport deviation value sequence F; If f i >F1, the i-th dispatch sub-path generates a first-level warning instruction at the current monitoring time node; Generate the operation risk value g based on all the transport deviation values; g=e3*Q3*[ (j i *h i )]+e4*Q4*[ (w i *f i )]; Among them, e3 is the preset third weight coefficient; e4 is the preset fourth weight coefficient; Q3 is the preset third fixed coefficient; Q4 is the preset fourth fixed coefficient; r is the number of coal categories; j i is the impact factor of the i-th coal category; h i is the risk value of coal shortage of the ith coal category generated based on all transportation deviation values; w i is the impact factor of the i-th transport sub-path; f i is the transfer deviation value of the i-th transfer sub-path at the current monitoring time node; n is the number of transfer orders; Preset operation risk value threshold G1; If g>G1, generate a secondary warning instruction.
[0017] Compared with the prior art, the method and system for visualizing the entire coal transportation cycle in the embodiment of the present application has the following beneficial effects: By periodically analyzing all transfer order parameters, we can establish transfer sub-paths for each ship in transit, monitor the transportation status of each ship in real time through Gantt charts, and visually compare the differences between the transfer plan and the actual execution status, making it convenient for managers to query. At the same time, we can promptly issue early warnings for abnormal problems in the transfer process, thereby dynamically adjusting the overall transfer plan, reducing overall transfer costs, and improving the management efficiency of coal transfer.
[0018] Evaluate a single transport sub-path and establish multiple monitoring points to comprehensively monitor the transport sub-path. Generate a deviation evaluation value for the transport sub-path based on the real-time data of each monitoring point, and promptly warn of the delay risk of the current transport sub-path, making it easier for managers to revise the transport plan. BRIEF DESCRIPTION OF THE DRAWINGS
[0019] Figure 1 It is a flow chart of a method for visualizing the entire cycle of coal transportation in a preferred embodiment of the present application. DETAILED DESCRIPTION
[0020] The following embodiments are used to illustrate the present invention, but are not intended to limit the scope of the present invention.
[0021] In the description of this application, it should be understood that the terms "center", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating the orientation or position relationship, are based on the orientation or position relationship shown in the accompanying drawings, and are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on this application.
[0022] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of the technical features being referred to. Thus, a feature specified as "first" or "second" may explicitly or implicitly include one or more of such features. Throughout this application, unless otherwise specified, "plurality" means two or more.
[0023] In the description of this application, it should be noted that, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. For example, they can refer to fixed connections, detachable connections, or integral connections; mechanical connections or electrical connections; direct connections or indirect connections through an intermediate medium; and internal connections between two components. Those skilled in the art will understand the specific meanings of the above terms in this application based on the specific circumstances.
[0024] like Figure 1 As shown, a method for visualizing the entire coal transportation cycle according to a preferred embodiment of the present application includes: S101: Setting multiple transfer sub-paths according to the acquired transfer order parameters; S102: Acquire monitoring data packets of each dispatch sub-path according to a preset monitoring time node, and generate dispatch deviation values of each dispatch sub-path; S103: Generate a monitoring display diagram, and determine whether to generate an early warning instruction based on all the dispatch deviation values.
[0025] Specifically, when setting multiple transport sub-paths, it includes: Traverse the transfer order parameters according to the preset update time node; Create a transfer order sequence B, B=(b1,b2…b i …b n ), where b i is the i-th transfer order; n is the number of transfer orders; According to the transfer order sequence B, set bi as the target transfer order in sequence; Obtain transaction data of the target transfer order; Generate the expected transfer trajectory of the target transfer order based on transaction data; Set up multiple monitoring points within the expected transportation trajectory; Generate the transport sub-path of the target transport order based on the expected transport trajectory and all monitoring points; Generate the transfer sub-paths for each transfer order in sequence; Establish a sequence of transport sub-paths A, A=(a1, a2…a i …a n ), where a i is the i-th transport subpath.
[0026] Specifically, by setting multiple update time nodes to continuously update the transfer order parameters, the completed transfer orders are eliminated, and the transfer sub-paths of the newly added transfer orders are established.
[0027] Specifically, by analyzing the transaction content in the transfer order, the expected travel path of the ship corresponding to the current transfer order is generated, and the location points on the expected travel path that may interfere with the transportation time (for example, loading ports, unloading ports, and environmental hazard points on the transportation route) are set as monitoring points through historical parameters.
[0028] Specifically, by establishing multiple monitoring points, management personnel can analyze the actual transportation time of each transportation sub-route, thereby improving the management efficiency of coal transportation.
[0029] It can be understood that in the above embodiment, by periodically analyzing all the transfer order parameters, the transfer sub-paths of each ship in transit are established, the transportation status of each ship is monitored in real time through the Gantt chart, and the difference between the transfer plan and the actual execution status is visually compared, which is convenient for management personnel to query. At the same time, abnormal problems in the transfer process can be warned in time, thereby dynamically adjusting the overall transfer plan, reducing the overall transfer cost, and improving the management efficiency of coal transfer.
[0030] In a preferred embodiment of the present application, generating the transport deviation value of each transport sub-path includes: Set a in sequence according to the transport sub-path A i Transport subpaths to the target; Obtain the monitoring data packet of the target dispatch sub-path at the current monitoring time node; Generate the real-time position of the vessel within the target transport sub-path based on the monitoring data packet; Generate the progress deviation value U of the target dispatch sub-path at the current monitoring time node based on the real-time position; Generate the remaining running path of the target dispatch sub-path at the current monitoring time node based on the real-time location; Set all monitoring points within the remaining operation path as first-level monitoring points; Establish a first-level monitoring point sequence P, P=(p1, p2…p i …p m ), where p i is the i-th first-level monitoring point in the remaining operation path; m is the number of first-level monitoring points in the remaining operation path; Generate interference evaluation values for each first-level monitoring point; Establish the interference evaluation value sequence C, C=(c1,c2…c i …c m ), where c i is the interference evaluation value of the i-th first-level monitoring point; Generate the dispatch deviation value f of the target dispatch subpath at the current monitoring time node based on the progress deviation value U and the interference evaluation value sequence C; Generate the transport deviation value of each transport sub-path at the current monitoring time node in sequence; Establish the sequence of deviation values F, F=(f1,f2…f i …f n ), where f i is the dispatch deviation value of the i-th dispatch sub-path at the current monitoring time node.
[0031] Specifically, generating the dispatch deviation value f of the target dispatch subpath at the current monitoring time node includes: f=e1*Q1*U+e2*Q2* (β i *c i ); Wherein, e1 is the preset first weight coefficient; e2 is the preset second weight coefficient; Q1 is the preset first fixed coefficient; Q2 is the preset second fixed coefficient; β i is the impact factor of the i-th first-level monitoring point in the remaining operation path.
[0032] Specifically, all parameters in the model are normalized by presetting a first fixed coefficient and a second fixed coefficient, so that each parameter in the model is in the same value range.
[0033] Specifically, the larger the progress deviation value U, the greater the difference between the real-time transportation progress of the ships in the current target transportation sub-path at the current monitoring time node and the expected transportation progress, that is, the greater the possibility that the ships in the target transportation sub-path will be delayed in arriving at the port.
[0034] Specifically, the interference evaluation value of each first-level monitoring point is generated, including: According to the first-level monitoring point sequence P, set p i It is the target first-level monitoring point; Generate the expected time point for the ship in the target transportation sub-path to arrive at the target first-level monitoring point; Generate characteristic data of the target first-level monitoring point at the expected time point based on the preset monitoring model; Generate the interference evaluation value c of the target first-level monitoring point; c=t*[ η i *Y(i)*(k i -k' i )]; Where t is the compensation coefficient generated based on the credibility of the preset monitoring model; θ is the number of interference indicators at the target first-level monitoring point; η i is the influencing factor of the i-th interference index of the target first-level monitoring point; k i is the real-time reference value of the interference index of the target first-level monitoring point generated based on the characteristic data; k'i is the standard reference value of the interference index of the target first-level monitoring point; Y(i) is the selection coefficient; if (k i -k' i )>0,Y(i)=1; if(k i -k' i )<0,Y(i)=0; Generate the interference evaluation value of each first-level monitoring point in turn.
[0035] Specifically, interference indicators include but are not limited to environmental factors, such as whether there are typhoons, heavy rains, etc., the congestion level of the monitoring point, whether there is traffic control, terminal status, loading and unloading efficiency, vessel waiting time and other parameters.
[0036] Specifically, the preset monitoring model consists of an environmental data collection model and a port simulation model.
[0037] It can be understood that in the above embodiment, a single transport sub-path is evaluated and multiple monitoring points are established to comprehensively monitor the transport sub-path. A deviation evaluation value of the transport sub-path is generated based on the real-time data of each monitoring point, and a timely warning of the delay risk of the current transport sub-path is issued, making it convenient for management personnel to correct the transport plan.
[0038] In a preferred embodiment of the present application, generating a monitoring display diagram includes: Create an initial display image; Set the display parameters of each transport sub-path according to the transport deviation value sequence F; Generate coal category sequence D according to historical coal burning parameters, D=(d1,d2…d i …d r ), where d i is the i-th coal category; r is the number of coal categories; Establish an association network based on the coal category sequence D and the transportation sub-path sequence A; Based on the initial display diagram, the ecological monitoring display diagram of the display parameters of the association network and each transportation sub-path is displayed.
[0039] Specifically, the greater the deviation evaluation value, the greater the possibility of transportation delay in the current transportation sub-route. Its position on the monitoring display needs to be closer, and the corresponding display color should be brighter, so as to facilitate management personnel to query and monitor.
[0040] Specifically, by establishing a network of relationships, comprehensive management of transportation sub-routes and on-site inventory can be achieved, avoiding shortages of a single type of coal or excessive inventory pressure, and improving the monitoring efficiency of the entire coal cycle.
[0041] Specifically, whether to generate an early warning instruction is determined based on all the transport deviation values, including: Preset the first transport deviation threshold F1; Get the transport deviation value sequence F; If f i >F1, the i-th dispatch sub-path generates a first-level warning instruction at the current monitoring time node; Generate the operation risk value g based on all the transport deviation values; g=e3*Q3*[ (j i *h i )]+e4*Q4*[ (w i *f i )]; Among them, e3 is the preset third weight coefficient; e4 is the preset fourth weight coefficient; Q3 is the preset third fixed coefficient; Q4 is the preset fourth fixed coefficient; r is the number of coal categories; j i is the impact factor of the i-th coal category; h i is the risk value of coal shortage of the ith coal category generated based on all transportation deviation values; w i is the impact factor of the i-th transport sub-path; f i is the transfer deviation value of the i-th transfer sub-path at the current monitoring time node; n is the number of transfer orders; Preset operation risk value threshold G1; If g>G1, generate a secondary warning instruction.
[0042] Specifically, the first-level warning instruction refers to correcting the transportation parameters of the remaining operating paths of the current transfer sub-path, so as to avoid delays in the current transfer sub-path.
[0043] Specifically, the second-level early warning instruction refers to dynamically revising the overall call plan by analyzing all transportation sub-paths and internal inventory parameters of the factory, thereby reducing overall transportation and management costs.
[0044] Specifically, all parameters in the model are normalized by presetting the third fixed coefficient and the fourth fixed coefficient, so that each parameter is in the same value range.
[0045] Based on another preferred embodiment of a method for visualizing the entire coal transportation cycle in any of the above preferred embodiments, this preferred embodiment provides a method for visualizing the entire coal transportation cycle, including: The central control unit sets multiple transfer sub-paths based on the obtained transfer order parameters; Monitoring unit, used to collect multi-source data; The monitoring unit is further used to generate monitoring data packets for each dispatch sub-path according to preset monitoring time nodes; The central control unit includes: The first processing module is used to set multiple transportation sub-paths; The second processing module generates a dispatch deviation value for each dispatch sub-path according to all monitoring data packets; The early warning module is used to determine whether to generate an early warning instruction based on all the transportation deviation values; A display module, used for generating a monitoring display graph; The first processing module is further configured to: Traverse the transfer order parameters according to the preset update time node; Create a transfer order sequence B, B=(b1,b2…b i …b n ), where b i is the i-th transfer order; n is the number of transfer orders; According to the transfer order sequence B, set bi as the target transfer order in sequence; Obtain transaction data of the target transfer order; Generate the expected transfer trajectory of the target transfer order based on transaction data; Set up multiple monitoring points within the expected transportation trajectory; Generate the transport sub-path of the target transport order based on the expected transport trajectory and all monitoring points; Generate the transfer sub-paths for each transfer order in sequence; Establish a sequence of transport sub-paths A, A=(a1, a2…a i …a n ), where a i is the i-th transport subpath.
[0046] Specifically, the second processing module is further configured to: Set a in sequence according to the transport sub-path A i Transport subpaths to the target; Obtain the monitoring data packet of the target dispatch sub-path at the current monitoring time node; Generate the real-time position of the vessel within the target transport sub-path based on the monitoring data packet; Generate the progress deviation value U of the target dispatch sub-path at the current monitoring time node based on the real-time position; Generate the remaining running path of the target dispatch sub-path at the current monitoring time node based on the real-time location; Set all monitoring points within the remaining operation path as first-level monitoring points; Establish a first-level monitoring point sequence P, P=(p1, p2…p i …p m ), where pi is the i-th first-level monitoring point in the remaining operation path; m is the number of first-level monitoring points in the remaining operation path; Generate interference evaluation values for each first-level monitoring point; Establish the interference evaluation value sequence C, C=(c1,c2…c i …c m ), where c i is the interference evaluation value of the i-th first-level monitoring point; Generate the dispatch deviation value f of the target dispatch subpath at the current monitoring time node based on the progress deviation value U and the interference evaluation value sequence C; Generate the transport deviation value of each transport sub-path at the current monitoring time node in sequence; Establish the sequence of deviation values F, F=(f1,f2…f i …f n ), where f i is the dispatch deviation value of the i-th dispatch sub-path at the current monitoring time node.
[0047] Specifically, the early warning module is also used to: Preset the first transport deviation threshold F1; Get the transport deviation value sequence F; If f i >F1, the i-th dispatch sub-path generates a first-level warning instruction at the current monitoring time node; Generate the operation risk value g based on all the transport deviation values; g=e3*Q3*[ (j i *h i )]+e4*Q4*[ (w i *f i )]; Among them, e3 is the preset third weight coefficient; e4 is the preset fourth weight coefficient; Q3 is the preset third fixed coefficient; Q4 is the preset fourth fixed coefficient; r is the number of coal categories; j i is the impact factor of the i-th coal category; h i is the risk value of coal shortage of the ith coal category generated based on all transportation deviation values; w i is the impact factor of the i-th transport sub-path; f i is the transfer deviation value of the i-th transfer sub-path at the current monitoring time node; n is the number of transfer orders; Preset operation risk value threshold G1; If g>G1, generate a secondary warning instruction.
[0048] According to the first concept of this application, by periodically analyzing all the transfer order parameters, the transfer sub-paths of each ship in transit are established, and the transportation status of each ship is monitored in real time through the Gantt chart. The difference between the transfer plan and the actual execution status can be visually compared to facilitate inquiries by management personnel. At the same time, early warnings can be issued for abnormal problems in the transfer process in a timely manner, thereby dynamically adjusting the overall transfer plan, reducing the overall transfer cost, and improving the management efficiency of coal transfer.
[0049] According to the second concept of this application, a single transfer sub-path is evaluated and multiple monitoring points are established to comprehensively monitor the transfer sub-path. A deviation evaluation value of the transfer sub-path is generated based on the real-time data of each monitoring point, and a timely warning of the delay risk of the current transfer sub-path is issued, making it convenient for management personnel to correct the transfer plan.
[0050] The above is only a preferred embodiment of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and replacements can be made without departing from the technical principles of the present application. These improvements and replacements should also be regarded as the scope of protection of the present application.
Claims
1. A method for visualizing the entire coal transportation cycle, characterized in that: include: Set multiple transfer sub-paths based on the obtained transfer order parameters; Obtain monitoring data packets for each dispatch sub-path according to preset monitoring time nodes, and generate dispatch deviation values for each dispatch sub-path; Generate a monitoring display diagram and determine whether to generate an early warning instruction based on all transportation deviation values.
2. The method for visualizing the entire coal transportation cycle according to claim 1, characterized in that: When setting multiple transport sub-paths, include: Traverse the transfer order parameters according to the preset update time node; Create a transfer order sequence B, B=(b1,b2…b i …b n ), where b i is the i-th transfer order; n is the number of transfer orders; According to the transfer order sequence B, set bi as the target transfer order in sequence; Obtain transaction data of the target transfer order; Generate the expected transfer trajectory of the target transfer order based on transaction data; Set up multiple monitoring points within the expected transportation trajectory; Generate the transport sub-path of the target transport order based on the expected transport trajectory and all monitoring points; Generate the transfer sub-paths for each transfer order in sequence; Establish a sequence of transport sub-paths A, A=(a1, a2…a i …a n ), where a i is the i-th transport subpath.
3. The method for visualizing the entire coal transportation cycle according to claim 2, characterized in that: When generating the transport deviation value for each transport sub-path, the following are included: Set a in sequence according to the transport sub-path A i Transport subpaths to the target; Obtain the monitoring data packet of the target dispatch sub-path at the current monitoring time node; Generate the real-time position of the ship within the target transport sub-path based on the monitoring data packet; Generate the progress deviation value U of the target dispatch sub-path at the current monitoring time node based on the real-time position; Generate the remaining running path of the target dispatch sub-path at the current monitoring time node based on the real-time location; Set all monitoring points within the remaining operation path as first-level monitoring points; Establish a first-level monitoring point sequence P, P=(p1, p2…p i …p m ), where p i is the i-th first-level monitoring point in the remaining operation path; m is the number of first-level monitoring points in the remaining operation path; Generate interference evaluation values for each first-level monitoring point; Establish the interference evaluation value sequence C, C=(c1,c2…c i …c m ), where c i is the interference evaluation value of the i-th first-level monitoring point; Generate the dispatch deviation value f of the target dispatch subpath at the current monitoring time node based on the progress deviation value U and the interference evaluation value sequence C; Generate the transport deviation value of each transport sub-path at the current monitoring time node in sequence; Establish the sequence of deviation values F, F=(f1,f2…f i …f n ), where f i is the dispatch deviation value of the i-th dispatch sub-path at the current monitoring time node.
4. The method for visualizing the entire coal transportation cycle according to claim 3, characterized in that: Generate the dispatch deviation value f of the target dispatch subpath at the current monitoring time node, including: f=e1*Q1*U+e2*Q2* (β i *c i ); Among them, e1 is the preset first weight coefficient; e2 is the preset second weight coefficient; Q1 is the preset first fixed coefficient; Q2 is the preset second fixed coefficient; β i is the impact factor of the i-th first-level monitoring point in the remaining operation path.
5. The method for visualizing the entire coal transportation cycle according to claim 4, characterized in that: Generate interference evaluation values for each first-level monitoring point, including: According to the first-level monitoring point sequence P, set p i It is the target first-level monitoring point; Generate the expected time point for the ship in the target transportation sub-path to arrive at the target first-level monitoring point; Generate characteristic data of the target first-level monitoring point at the expected time point based on the preset monitoring model; Generate the interference evaluation value c of the target first-level monitoring point; c=t*[ η i *Y(i)*(k i -k' i )]; Where t is the compensation coefficient generated based on the credibility of the preset monitoring model; θ is the number of interference indicators at the target first-level monitoring point; η i is the influencing factor of the i-th interference index of the target first-level monitoring point; k i is the real-time reference value of the interference index of the target first-level monitoring point generated based on the characteristic data; k' i is the standard reference value of the interference index of the target first-level monitoring point; Y(i) is the selection coefficient; if (k i -k' i )>0,Y(i)=1; if(k i -k' i )<0,Y(i)=0; Generate the interference evaluation value of each first-level monitoring point in turn.
6. The method for visualizing the entire coal transportation cycle according to claim 3, characterized in that: Generate monitoring display diagrams, including: Create an initial display image; Set the display parameters of each transport sub-path according to the transport deviation value sequence F; Generate coal category sequence D according to historical coal burning parameters, D=(d1,d2…d i …d r ), where d i is the i-th coal category; r is the number of coal categories; Establish an association network based on the coal category sequence D and the transportation sub-path sequence A; Based on the initial display diagram, the display parameters of the association network and each dispatch sub-path are ecologically formed into a monitoring display diagram.
7. The method for visualizing the entire coal transportation cycle according to claim 6, characterized in that: Determine whether to generate an early warning instruction based on all transportation deviation values, including: Preset the first transport deviation threshold F1; Get the transport deviation value sequence F; If f i >F1, the i-th dispatch sub-path generates a first-level warning instruction at the current monitoring time node; Generate the operation risk value g based on all the transport deviation values; g=e3*Q3*[ (j i *h i )]+e4*Q4*[ (w i *f i )]; Among them, e3 is the preset third weight coefficient; e4 is the preset fourth weight coefficient; Q3 is the preset third fixed coefficient; Q4 is the preset fourth fixed coefficient; r is the number of coal categories; j i is the impact factor of the i-th coal category; h i is the risk value of coal shortage of the ith coal category generated based on all transportation deviation values; w i is the impact factor of the i-th transport sub-path; f i is the transfer deviation value of the i-th transfer sub-path at the current monitoring time node; n is the number of transfer orders; Preset operation risk value threshold G1; If g>G1, generate a secondary warning instruction.
8. A full-cycle visualization system for coal transportation, using the full-cycle visualization method for coal transportation according to any one of claims 1 to 7, characterized in that: include: The central control unit sets multiple transfer sub-paths based on the obtained transfer order parameters; Monitoring unit, used to collect multi-source data; The monitoring unit is further configured to generate a monitoring data packet for each dispatch sub-path according to a preset monitoring time node; The central control unit includes: The first processing module is used to set multiple transportation sub-paths; The second processing module generates a dispatch deviation value for each dispatch sub-path based on all monitoring data packets; The early warning module is used to determine whether to generate an early warning instruction based on all the transportation deviation values; A display module, used for generating a monitoring display graph; The first processing module is further configured to: Traverse the transfer order parameters according to the preset update time node; Create a transfer order sequence B, B=(b1,b2…b i …b n ), where b i is the i-th transfer order; n is the number of transfer orders; According to the transfer order sequence B, set bi as the target transfer order in sequence; Obtain transaction data of the target transfer order; Generate the expected transfer trajectory of the target transfer order based on transaction data; Set up multiple monitoring points within the expected transportation trajectory; Generate the transport sub-path of the target transport order based on the expected transport trajectory and all monitoring points; Generate the transfer sub-paths for each transfer order in sequence; Establish a sequence of transport sub-paths A, A=(a1, a2…a i …a n ), where a i is the i-th transport subpath.
9. The full-cycle visualization system for coal transportation according to claim 8, characterized in that: The second processing module is further configured to: Set a in sequence according to the transport sub-path A i Transport subpaths to the target; Obtain the monitoring data packet of the target dispatch sub-path at the current monitoring time node; Generate the real-time position of the ship within the target transport sub-path based on the monitoring data packet; Generate the progress deviation value U of the target dispatch sub-path at the current monitoring time node based on the real-time position; Generate the remaining running path of the target dispatch sub-path at the current monitoring time node based on the real-time location; Set all monitoring points within the remaining operation path as first-level monitoring points; Establish a first-level monitoring point sequence P, P=(p1, p2…p i …p m ), where p i is the i-th first-level monitoring point in the remaining operation path; m is the number of first-level monitoring points in the remaining operation path; Generate interference evaluation values for each first-level monitoring point; Establish the interference evaluation value sequence C, C=(c1,c2…c i …c m ), where c i is the interference evaluation value of the i-th first-level monitoring point; Generate the dispatch deviation value f of the target dispatch subpath at the current monitoring time node based on the progress deviation value U and the interference evaluation value sequence C; Generate the transport deviation value of each transport sub-path at the current monitoring time node in sequence; Establish the sequence of deviation values F, F=(f1,f2…f i …f n ), where f i is the dispatch deviation value of the i-th dispatch sub-path at the current monitoring time node.
10. The full-cycle visualization system for coal transportation according to claim 9, characterized in that: The early warning module is also used for: Preset the first transport deviation threshold F1; Get the transport deviation value sequence F; If f i >F1, the i-th dispatch sub-path generates a first-level warning instruction at the current monitoring time node; Generate the operation risk value g based on all the transport deviation values; g=e3*Q3*[ (j i *h i )]+e4*Q4*[ (w i *f i )]; Among them, e3 is the preset third weight coefficient; e4 is the preset fourth weight coefficient; Q3 is the preset third fixed coefficient; Q4 is the preset fourth fixed coefficient; r is the number of coal categories; j i is the impact factor of the i-th coal category; h i is the risk value of coal shortage of the ith coal category generated based on all transportation deviation values; w i is the impact factor of the i-th transport sub-path; f i is the transfer deviation value of the i-th transfer sub-path at the current monitoring time node; n is the number of transfer orders; Preset operation risk value threshold G1; If g>G1, generate a secondary warning instruction.