Mine Management System

Abstract

To provide a mine management system capable of accurately and easily classifying a travel route of mining vehicle.SOLUTION: With respect to a mesh set A of unclassified travel routes, which are unclassified travel routes, and a mesh set B of classified travel routes, which are classified travel routes, the mine management system calculates a union of the mesh set A and the mesh set B, a first difference set between the union and the mesh set A, and a second difference set between the union and the mesh set B. When the magnitude of the first difference set and the second difference set are both equal to or less than a threshold, the unclassified travel route is classified into the route ID of the classified travel route, and when at least one of the magnitudes of the first difference set and the second difference set is greater than the threshold, the unclassified travel route is classified into a new route ID.SELECTED DRAWING: Figure 4

Description

[Technical Field]

[0001] The present invention relates to a mine management system. [Background technology]

[0002] Patent Document 1 discloses a method for identifying a travel route by comparing position information of multiple intermediate points on the travel route traveled by a mining vehicle with position information of a predetermined designated route. Patent Document 2 discloses a method for correcting position data of dump sites and the like, which are basic information for route classification, after classifying the travel route. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent No. 5596661 [Patent Document 2] Patent No. 5647362 Summary of the Invention [Problem to be solved by the invention]

[0004] The travel route of a mining vehicle measured by GNSS may appear to deviate from the designated route to which it should be classified, for example, when there is an error in the GNSS data or when the mining vehicle travels while avoiding other vehicles or rough roads. Therefore, with the technology of Patent Document 1, depending on the positioning of the comparison points of the designated route to be compared with intermediate points of the travel route, the travel route may be classified as a route different from the route to which it should be classified, resulting in an inappropriate evaluation of productivity. In contrast, using more comparison points, as in Patent Document 2, can improve the accuracy of route classification. However, the more comparison points there are, the more complicated it becomes to set a distance threshold for each comparison point, and it becomes more difficult to set comparison points while avoiding interference with other designated routes.

[0005] In addition, in mining sites, routes that differ from the designated route but completely match a portion of the designated route (inclusions) and routes that deviate from the designated route and stop at rest areas (detours) may actually occur. Regarding these inclusions and detours, the technologies of Patent Documents 1 and 2 require the direction and travel distance of the links connecting the comparison points to be added as route classification conditions, further complicating the route classification process. Furthermore, if the route to be evaluated does not match any of the designated routes, new dumping sites, loading sites, and comparison points must be set to establish a new designated route, and distance thresholds for determining whether the route has been passed must be set for each point.

[0006] Since dumping sites and loading sites move frequently at mine sites, the technologies of Patent Documents 1 and 2 require frequent updates to the settings of dumping sites, loading sites, and even comparison points, which can require a lot of effort to operate the system.

[0007] An object of the present invention is to provide a mine management system that can easily classify the travel routes of mine vehicles with high accuracy. [Means for solving the problem]

[0008] In order to achieve the above object, the present invention provides a mine management system that includes a processing device that generates a mesh set represented by IDs of meshes that divide the earth's surface at equal intervals for a travel route that starts at a location where the mine vehicle has dumped earth and ends at a location where the mine vehicle will next dump earth, based on position data and operation data of the mine vehicle, and has the function of classifying route IDs based on the mesh set, a storage device that stores and accumulates the mesh set and the operation data for the travel route generated by the processing device in association with each other, and a display terminal device that exchanges data with the processing device and displays data received from the processing device, and the processing device classifies the route IDs for a mesh set A of unclassified travel routes that are unclassified travel routes and a mesh set B of classified travel routes that are classified, and mesh set B, a first difference set which is the logical difference between the union and mesh set A, and a second difference set which is the logical difference between the union and mesh set B; if the sizes of the first difference set and the second difference set are each equal to or smaller than a preset threshold, the unclassified travel route is classified into a route ID of the classified travel route, and the route ID is linked to the mesh set A and the operation data related to the unclassified travel route and recorded in the storage device; if at least one of the sizes of the first difference set and the second difference set is larger than the threshold, a new route ID is generated, and the mesh set A and the operation data related to the unclassified travel route are linked to the new route ID and recorded in the storage device. [Effects of the Invention]

[0009] According to the present invention, the travel routes of mining vehicles can be classified easily and with high accuracy. [Brief explanation of the drawings]

[0010] [Figure 1] 1 is a schematic diagram showing an overall view of a mine management system according to the present invention; [Figure 2] FIG. 1 is a block diagram illustrating a function of recording productivity index data of a processing device constituting a mine management system according to a first embodiment of the present invention in association with a route ID. [Figure 3] An explanatory diagram of a mesh set representing a travel route in the present invention. [Figure 4] Venn diagram showing the basic concept of the driving path determination algorithm according to the present invention [Figure 5] A Venn diagram showing examples of cases where the processing device constituting the mine management system according to the first embodiment of the present invention determines that two travel routes relating to mesh sets A and B are the same route and cases where the processing device determines that two travel routes are different routes. [Figure 6] 1 is a flowchart showing an example of a route classification procedure of a mine management system according to a first embodiment of the present invention. [Figure 7] Comparison table between the mine management system according to the first embodiment of the present invention and the so-called node-link mine management system [Figure 8] FIG. 1 is an example of a block diagram relating to a function of calculating an aggregate value of a productivity index for each route of a processing device constituting a mine management system according to a first embodiment of the present invention. [Figure 9] A flowchart showing an example of a procedure for presenting recommended control parameters based on the aggregation results of productivity indexes of processing devices that constitute the mine management system according to the first embodiment of the present invention. [Figure 10A] A diagram showing an example of a screen presenting candidates for evaluation route IDs. [Figure 10B] An example of a screen that visualizes a mesh set linked to an evaluation route ID. [Figure 11A] An example of a screen showing the travel frequency for each control parameter for the selected evaluation route ID in a bar graph. [Figure 11B] Example of a screen showing a comparison of productivity by control parameters for the selected evaluation route ID [Figure 11C] An example of a screen showing a histogram of the frequency of travel for standard parameters and alternative parameters for the same productivity indicator for the selected evaluation route ID. [Figure 11D] Example of a screen showing the difference in productivity depending on control parameters for multiple routes [Figure 12]A flowchart showing an example of a procedure for determining a deteriorated vehicle of a processing device constituting a mine management system according to a second embodiment of the present invention. [Figure 13A] FIG. 10 is a diagram illustrating an example of a screen displaying the productivity of each vehicle ID that traveled along a selected route ID. [Figure 13B] A diagram showing a histogram of predetermined operational data for each cycle in the evaluation path. [Figure 14] FIG. 10 is a conceptual diagram illustrating an omnidirectional mesh used in a mine management system according to a third embodiment of the present invention. [Figure 15] Schematic diagram for explaining an example of route classification using an omnidirectional mesh [Figure 16] A flowchart showing an example of a procedure for deleting a route ID with a low travel frequency of a processing device constituting a mine management system according to a fourth embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0011] Hereinafter, an embodiment of the present invention will be described with reference to the drawings.

[0012] (overview) FIG. 1 is a schematic diagram showing an overall view of a mine management system according to the present invention. The mine management system 1 shown in FIG. 1 has the function of receiving operational data and position data for each mining vehicle V operating at a mine site S and evaluating the productivity of the mine site. The mining vehicles V operating at the mine site S include multiple types of vehicles, such as mining dump trucks V1, hydraulic excavators V2, and bulldozers V3. Furthermore, at the mine site S, even mining vehicles V of the same type (e.g., mining dump trucks V1) may be mixed together with vehicles of different manufacturers, models, and manufacturing dates. The terrain on which the mining vehicles V travel varies in undulations and characteristics depending on the route, and differences in model and manufacturing date result in differences in fuel consumption, climbing speed, and other factors. Because these differences affect the productivity of the mine site S, it is important to manage the productivity of the mine site S using a mine management system.

[0013] The mine management system shown in FIG. 1 includes a processing device 10, a storage device 20, and a display terminal device 30.

[0014] The processing device 10 is, for example, a computer (such as a server) located at the mine site S or a location away from the mine site S. This processing device 10 is configured to be able to exchange data with each mining vehicle V, the storage device 20, and the display terminal device 30 respectively. For example, log data such as the position data and operation data of each mining vehicle V received via the network, and various request data from the display terminal device 30 are input to the processing device 10. The position data of each mining vehicle V is the output of a positioning device (such as a GNSS rover) mounted on each mining vehicle V. The operation data is the output of various sensors (not shown) mounted on the mining vehicle V. For example, in the case of the mining dump V1, it is the output of a weighing scale (such as a load cell) that measures the loading weight and a fuel sensor (such as a liquid level gauge) that measures the remaining fuel amount. In addition, it can also include control parameters (described later) applied to vehicle control, etc. The request data is a signal requesting various data displays according to the operation of the display terminal device 30. Also, the processing device 10 records data in the storage device 20 or reads data from the storage device 20.

[0015] In particular, the processing device 10 of the present embodiment is equipped with a function of classifying the travel routes of each mining vehicle V at the mine site S for each route ID based on the position data and operation data of each mining vehicle V.

[0016] In this specification, the "travel route" refers to the route traveled from one dumping site to the next dumping site. That is, a route starting from one dumping site where a mining vehicle V has dumped its load and ending at the next dumping site (the place where the load loaded at a predetermined loading site after dumping at one dumping site is dumped) is the travel route. The dumping of the mining vehicle V can be determined based on the change in the output of the weighing scale mounted on the mining vehicle V. For example, when the loading weight above the set value m1 decreases to below the set value m2 (m2 < m1), it is determined that the load has been dumped. The travel route of the mining vehicle V is specified from the position data sequentially output from the positioning device mounted on the mining vehicle V.

[0017] In addition, in the following, when the term "cycle" is used, it refers to the process that the mining vehicle V performs from the start point to the end point of its travel route, that is, the series of processes of moving from one dumping site to a loading site, loading the cargo, moving to the next dumping site for dumping, and then dumping the soil.

[0018] In each embodiment, the travel route of the mining vehicle V is defined by a mesh set that divides the ground surface at equal intervals, that is, a mesh set that is represented by the IDs of multiple meshes at points that the vehicle enters as it travels. The mesh set that defines the travel route is generated by the processing device 10 for each mining vehicle V based on the data received from each positioning device, and is classified into one of the route IDs defined for the mining site S or a new route.

[0019] The processing device 10 also has the function of calculating mine productivity index data based on the position data and operation data of each mining vehicle V, and the function of determining the deterioration state of parts of each mining vehicle V and the quality of control parameters.

[0020] "Control parameters" are parameters related to the driving control of each mining vehicle V, such as the engine's idle speed, maximum speed, engine response, etc. For example, the maximum speed is generally related to engine output. The higher the maximum speed is set, the higher the climbing speed of the mining vehicle V, and the lower the maximum speed is set, the lower the climbing speed. The idle speed is related to the timing at which the vehicle speed begins to increase. The higher the idle speed is set, the shorter it takes for the mining vehicle V to start accelerating, and the lower the idle speed, the longer it takes to reach a specified engine speed. In addition, the operating feel changes depending on the engine response setting. The engine response is adjusted, for example, by a program in the ECU (Engine Control Unit).

[0021] In addition to standard parameters, the control parameters of the mining vehicle V also include several other parameters pre-stored as default values ​​in the storage device 20. The mining vehicle V travels through the mining site S with one of the default values ​​applied to each control parameter. The control parameters for the mining vehicle V are set, for example, by connecting a predetermined terminal device to the travel control device (controller) of the mining vehicle V and operating the connected terminal device to write and set the predetermined control parameters in the travel control device of the mining vehicle V. If the travel control device of the mining vehicle V has the function of applying received control parameters to itself, for example, the control parameters set by the display terminal device 30 can be recorded in the storage device 20 by the processing device 10 and transmitted to the mining vehicle V, and automatically applied to the mining vehicle V. Furthermore, it is possible to set control parameters individually for each mining vehicle V operating at the mining site S, but it is also possible to set common control parameters for all mining vehicles V operating at the mining site S, or to set different control parameters for each mining vehicle V, for example, for each route ID.

[0022] A "productivity index" is an item used to determine or evaluate the productivity of the mine site S. Specific examples of productivity indexes include the amount of cargo transported per liter of fuel (T / L) for each mining vehicle V, the amount transported per unit time (T / h), and the amount of fuel consumed per unit time (L / h). Other examples of productivity indexes include travel distance, travel time, and fuel efficiency. These productivity index data can be calculated, for example, as a value for each mining vehicle V operating at the mine site S during a specified period, a total value for all mining vehicles V, a value for each route ID, or a total value for all route IDs. The value of such a productivity index can vary depending on the control parameters applied to the mining vehicle V, even when the same mining vehicle V travels the same travel route.

[0023] For example, lowering the engine's maximum RPM reduces the mining vehicle V's climbing speed. Lowering the engine's idle RPM also slows the mining vehicle V's acceleration. In this case, the amount of cargo transported per unit time (T / h) decreases, which can contribute to reduced productivity. However, at a mining site (S), some speed differences are absorbed due to queues and traffic jams at the loading dock, and depending on the driving route, the maximum RPM setting may have little effect on the amount of cargo transported per unit time. On the other hand, lowering the engine's maximum RPM and idle RPM can reduce fuel consumption and improve the amount of cargo transported per liter of fuel (T / L) and the amount of fuel consumed per unit time (L / h). At a large mining site (S) with a large number of mining vehicles (V) in operation, the control parameters applied to each mining vehicle (V) can make a huge difference in the total annual fuel cost. It is desirable to set the control parameters by comprehensively considering the changes in each productivity index, while understanding how the settings of the control parameters will affect each productivity index.

[0024] The mine management system 1 is a useful system that can estimate how the value of each productivity index will change depending on the control parameters, and can present the user with the fluctuations in each productivity index due to the control parameters and recommended control parameters. In some cases, the mine management system 1 can be configured to transmit the calculated recommended control parameters to the mine vehicles V and apply them to each mine vehicle V.

[0025] It is desirable that the operation data and position data of the mining vehicle V be transmitted to the mine management system 1 in real time, but sequential transmission is not always possible depending on the communication conditions and communication costs at the mine site S. The processing device 10 can also be configured to sequentially process the input operation data, etc., when the operation data, etc., can be received sequentially. However, when the operation data, etc., cannot be received sequentially, the processing device 10 can also be configured to buffer a certain amount of operation data and process the buffered operation data. An example of a certain amount of data is the amount of data corresponding to the longest time between soil dumpings on past travel routes.

[0026] The storage device 20 (for example, a database) records and stores mesh sets, operation data, and vehicle IDs of the mining vehicles V linked to the travel routes generated by the processing device 10. The storage device 20 aggregates the position data and operation data of each mining vehicle V traveling in the same mining site S, which are managed collectively. The storage device 20 does not need to be a single storage device, and the storage device 20 may be made up of multiple storage devices connected via a network.

[0027] The display terminal device 30 is a computer equipped with a display device, typically a mobile computer such as a laptop computer, tablet terminal, or smartphone, which exchanges data with the processing device 10 and displays the data received from the processing device 10. The display terminal device 30 transmits a request signal for the desired display to the processing device 10 in response to an operation, receives responses from the processing device 10 such as productivity indicators for the mine site S, the deterioration state of each mining vehicle V, and the pass / fail status of the control parameters of each mining vehicle V, and displays these on the display device. A user of the mine management system 1 can check the data displayed on the display terminal device 30 to quickly grasp any declines or signs of decline in productivity at the mine site S, and can maintain and manage the productivity of the mine site S by taking measures according to the causes of the decline in productivity.

[0028] The display terminal device 30 can display information in various formats, such as report format and email format. In this embodiment, a dashboard format is used. For example, a mine operation manager P1 at the mine site S can view the time spent on each cycle on the dashboard information displayed on the display terminal device 30 and review the operation plan for each mine vehicle V. An operator instructor P2 can use the dashboard information to identify operators with poor driving skills, such as those who frequently make sudden starts and sudden brakes, and provide driving guidance. A road maintenance worker P3 can use the dashboard information to quickly identify areas of road surface roughness that may lead to reduced productivity and repair them. An equipment maintenance worker P4 can use the dashboard information to quickly identify deterioration or malfunction of onboard equipment on the mine vehicle V, perform prompt repairs, and calibrate control parameters to improve the fuel efficiency of the mine vehicle V according to the driving route. Furthermore, a mining manager P5 can check the dashboard information together with weather information (historical and / or forecast) and mineral prices (historical and / or forecast) obtained via the Internet IN, and revise mining plans and maintenance plans. Furthermore, based on the results of checking the dashboard information, etc., the mining manager P5 can instruct the operations manager P1, operator instructor P2, road surface maintenance worker P3, and equipment maintenance worker P4 on measures to prevent a decline in production.

[0029] (First embodiment) -Route classification and productivity index calculation functions- In the first embodiment, a system for notifying an equipment maintenance worker P4 of control parameters that improve productivity at a mining site S will be described.

[0030] 2 is an example of a block diagram of the processing device 10 relating to the function of recording the productivity index in association with the route ID. In FIG. 2, the functions of the processing device 10 for route classification and productivity index calculation are represented by blocks 11-13.

[0031] In block 11, the processing device 10 generates a mesh set for the travel route of each mining vehicle V traveling at the mining site S based on data such as position and load weight obtained from a positioning device, weighing scale, etc. mounted on the mining vehicle V. As described above, in this embodiment, a mesh set is generated each time a certain amount of data is buffered. The travel route for which a mesh set is generated in block 11 is a route whose route ID has not yet been classified, and will hereinafter be referred to as an "unclassified travel route."

[0032] In block 12, the processing device 10 classifies the unclassified travel route by comparing it with a mesh set linked to each route ID registered in the database 21 as a route table. The algorithm for classifying the unclassified travel route will be described later.

[0033] The database 21 is the storage device 20 or a part of its storage area. The database 21 stores mesh set data for each route ID in a table-type data structure, for example. The travel routes associated with the route IDs recorded in this database 21 are known routes that have been classified, and will hereinafter be referred to as "classified travel routes."

[0034] In block 12, if it is determined that the unclassified travel route corresponds to one of the route IDs already recorded in the database 21, the route ID of the corresponding classified route is output. Conversely, in block 12, if it is determined that the unclassified travel route does not correspond to any of the existing route IDs, a new route ID is output, and the mesh set of the unclassified travel route is linked to the new route ID and recorded in the database 21.

[0035] In block 13, the processing device 10 generates a mine productivity index (e.g., transport volume (T / L), transport volume (T / h)) and a cycle ID based on the operation data of the mining vehicle V related to the classified travel route (fuel consumption, cargo transport volume, travel distance, cycle start time, cycle end time, etc.). A "cycle ID" is an ID that is assigned each time the mining vehicle V performs a cycle; for example, the more frequently a route ID is traveled, the more cycle IDs are associated with it, resulting in a larger amount of data. The productivity index data and cycle ID generated here are associated with the route ID along with the vehicle ID and the control parameters applied to the mining vehicle V, and are recorded in the database 22 as a productivity table.

[0036] The database 22 is the storage device 20 or a part of its storage area. In the database 22, productivity index data, cycle IDs, vehicle IDs, and control parameters are recorded for each route ID, for example, in a table-type data structure. Based on this database 22, for example, the productivity index data of each mining vehicle V for a predetermined period can be evaluated for each route ID, and it is possible to determine whether a vehicle has reduced energy efficiency (a deteriorated vehicle) or whether adjustment of control parameters is necessary based on the relative merits of the productivity indexes for the same route ID.

[0037] -Route- FIG. 3 is an explanatory diagram of a set of meshes representing a travel route in the present invention. The example in FIG. 3 shows a schematic diagram of a travel route from dump site O, which is the starting position (starting point) of the cycle, to the next dump site D, which is the end position (end point) of the cycle. Here, the shape of each mesh is square (e.g., quadkey). However, as long as the mesh shape can cover the entire mine with the same shape, it can also be hexagonal (honeycomb) or rectangular (GeoHash). The dimensions of the mesh (longitude and latitude) are set so that the entire mine vehicle V can fit within the mesh and are longer than the travel distance of one sampling period of the positioning device at the mine vehicle V's maximum speed. In the case of a square mesh, the mesh size corresponds to, for example, a 30 x 30 m ground surface.

[0038] In Figure 3, the meshes that the mining vehicle V passed through on its way from dump site O to dump site D are shown surrounded by thick lines. The set of mesh IDs (m1, m2, ..., mx) of the multiple meshes surrounded by these thick lines is a mesh set that represents the travel route of the mining vehicle V. The travel route of the mining vehicle V is measured, for example, by a positioning device installed on the mining vehicle V, and a mesh set is generated by collecting the mesh IDs of the meshes that the mining vehicle V has passed through. Using such a mesh set eliminates the need for complicated setting of intermediate points or judgments using distance thresholds, and furthermore, route classification using set operations, which will be described later, can be easily realized.

[0039] -Basic concept of route determination- FIG. 4 is a Venn diagram illustrating the basic concept of the driving route determination algorithm according to the present invention. Consider a case where mesh set A of a first driving route is represented by a set of mesh IDs (m1, m2, m3, m4, m5, m6, ..., mx), and mesh set B of a second driving route is represented by a set of mesh IDs (m1, m2, m4, m6, ..., my). In this case, the following are calculated: union Σ (= A∪B), which is the logical sum of mesh sets A and B; first difference set Δ1 (= Σ-A), which is the logical difference between union Σ and mesh set A; and second difference set Δ2 (= Σ-B), which is the logical difference between union Σ and mesh set B. The magnitude of the first difference set Δ1 corresponds to the degree of mismatch between the second driving route and the first driving route, and the magnitude of the second difference set Δ2 corresponds to the degree of mismatch between the first driving route and the second driving route.

[0040] In this embodiment, the sizes of the first difference set Δ1 and the second difference set Δ2 are compared with thresholds S1 and S2 set respectively to determine whether the first travel route and the second travel route are the same or different routes. In other words, when determining whether the first travel route matches the second travel route, the size of the mismatch area between the two travel routes is evaluated to determine whether the two travel routes can be regarded as the same, rather than the size of the match area between the two travel routes. The degree of mismatch is not limited to the size of the first difference set Δ1 and the second difference set Δ2 themselves, and may be evaluated by converting it into, for example, the ratios R1 and R2 of the first difference set Δ1 and the second difference set Δ2 to the union Σ (R1 = Δ1 / Σ, R2 = Δ2 / Σ).

[0041] The size of the set is, for example, the number of meshes that make up the set, and the sizes of the first difference set Δ1 and the second difference set Δ2 correspond to the number of meshes that make up these difference sets.

[0042] - Route determination types - FIG. 5 is a Venn diagram showing examples of cases in which the processing device 10 determines that the two travel routes associated with the mesh sets A and B described in FIG. 4 are the same route and cases in which the processing device 10 determines that the two travel routes are different routes. The processing device 10 determines that the two travel routes associated with the mesh sets A and B are the same route when both the magnitudes of the first difference set Δ1 and the second difference set Δ2 (ratios R1 and R2 in this example) are equal to or smaller than preset thresholds S1 and S2, respectively. Conversely, the processing device 10 determines that the two travel routes associated with the mesh sets A and B are different routes when at least one of the magnitudes of the first difference set Δ1 and the second difference set Δ2 (ratios R1 and R2) is greater than the thresholds S1 and S2. The threshold S1 for the ratio R1 and the threshold S2 for the ratio R2 may be set to different values, but in this embodiment, a common value (e.g., 0.2) is set.

[0043] Using this determination algorithm, the processing device 10 determines that the two travel routes related to mesh sets A and B are the same route when the ratio R1 is equal to or less than the threshold value S1 and the ratio R2 is equal to or less than the threshold value S2, as in type a in Figure 5. In other cases, that is, when at least one of the ratios R1 and R2 is greater than the threshold value, the processing device 10 determines that the two travel routes related to mesh sets A and B are different routes. Types b, c, and d are shown in Figure 5 as typical cases in which at least one of the ratios R1 and R2 is greater than the threshold value.

[0044] Type b in Figure 5 is the case where the ratio R1 is greater than the threshold S1 and the ratio R2 is greater than the threshold S2, and it can be classified as type b when the two travel routes are completely different routes that do not even partially match, or when the two travel routes partially match but at least one of the dumping site and loading site is different. In the case of completely different routes, the Venn diagram is Δ1 = B, Δ2 = A.

[0045] Type c is a case where one of the ratios R1 and R2 is greater than the corresponding threshold value S1 or S2, and the other of the ratios R1 and R2 is equal to or less than the corresponding threshold value S1 or S2. Type c corresponds to a case where one travel route matches the other travel route to a certain extent, but the other travel route deviates significantly from the first travel route. For example, two travel routes are planned to have the same starting and ending points, but if a mining vehicle V deviates from the planned route on one of the travel routes due to a break or other reason (if there is a detour), mesh sets A and B may form a Venn diagram like that shown in type c. It may be desirable to distinguish the travel route of mesh set A shown in type c as an exception in data for evaluating the productivity of the travel route related to mesh set B.

[0046] Type d is the case where one of the ratios R1 and R2 is zero, and the other of the ratios R1 and R2 is greater than the corresponding threshold. Type d corresponds to the case where the entire travel route of one vehicle coincides with part of the travel route of the other vehicle (where one travel route is contained within the other vehicle). An example of this containment is when two dumping sites and loading sites on one travel route are all on the travel route of the other vehicle, and at least one of the two dumping sites on one travel route is located midway on the travel route of the other vehicle. The travel routes of mesh sets A and B shown in type c are different routes, so it is desirable to distinguish them.

[0047] -Route classification procedure- FIG. 6 is a flowchart showing an example of a procedure for route classification in the mine management system 1 according to this embodiment.

[0048] The processing device 10 classifies the routes of the unclassified travel routes related to the new data based on the position data and operation data newly acquired by each mining vehicle V each time the mining vehicle V travels through the mine site S, and records the new data in the storage device 20. The processing device 10 determines whether the unclassified travel route is the same route as a classified route, or whether it is a new route that does not fall under any of the classified routes, using mesh set A described in Fig. 4 as a mesh set of unclassified travel routes and mesh set B as a mesh set of classified travel routes recorded in the storage device 20.

[0049] The processing device 10 receives position data and operation data of each mining vehicle V at any time, and automatically executes the processing of the flowchart in FIG. 6 every time a certain amount of the data is buffered.

[0050] Step S601 When a certain amount of mesh IDs of passing meshes for new unclassified travel routes are buffered, the processing device 10 starts the process of FIG. 6 to generate a mesh set A of unclassified travel routes.

[0051] Step S602 After generating mesh set A, the processing device 10 calculates the above-mentioned union Σ, first difference set Δ1, and second difference set Δ2 for mesh set A of unclassified travel routes and mesh set B of classified travel routes (cycle IDs). In this embodiment, the processing device 10 further calculates the above-mentioned ratios R1 and R2 for each mesh set B as values ​​for evaluating the degree of mismatch between the unclassified travel routes related to mesh set A and the classified travel routes related to each mesh set B.

[0052] If there are multiple classified travel routes (cycle IDs), mesh set B for each classified cycle ID is compared with mesh set A, and the union Σ, first difference set Δ1, and second difference set Δ2 are calculated. However, if there are a large number of classified travel routes (for example, more than a preset number), the reduction in processing load on the processing device 10 may be excessive. In this case, a predetermined number (for example, the above-mentioned set number) or the total number of classified travel routes multiplied by a predetermined coefficient (for example, 0.2) may be extracted, and the union Σ, first difference set Δ1, and second difference set Δ2 may be calculated for each mesh set B of the extracted classified travel routes.

[0053] Then, the minimum value of the degree of mismatch between mesh sets A and B is identified. In this case, for example, mesh set B with the smallest average (or weighted average) or total value of ratios R1 and R2 (or Δ1 and Δ2) is identified, and the degree of mismatch related to the identified mesh set B can be identified as the minimum degree of mismatch. If there is only one classified driving route, the degree of mismatch related to this classified driving route will necessarily be the minimum degree of mismatch.

[0054] Step S603 After calculating the minimum discrepancy, the processing device 10 determines whether the unclassified travel route is a different route from or the same as the classified travel route (cycle ID) associated with the minimum discrepancy, based on whether the minimum discrepancy is greater than or equal to a preset threshold. Specifically, as described with reference to FIGS. 4 and 5, if both the first difference set Δ1 and the second difference set Δ2 (ratios R1 and R2 in this example) are less than or equal to preset thresholds S1 and S2 (e.g., 0.2), respectively, the discrepancy is determined to be less than or equal to the threshold (N), and the unclassified travel route and the classified travel route associated with the minimum discrepancy are determined to be the same route. In this case, the procedure proceeds from step S603 to step S606. On the other hand, if at least one of the first difference set Δ1 and the second difference set Δ2 (ratios R1 and R2 in this example) is greater than the thresholds S1 and S2, the discrepancy is determined to be greater than the threshold (Y), and the unclassified travel route and the classified travel route associated with the minimum discrepancy are determined to be different routes. In this case, the procedure moves from step S603 to step S604.

[0055] Step S604 If the minimum degree of mismatch is greater than the threshold value, the processing device 10 adds the unclassified route related to the mesh set A generated in step S601 as a new route, and records it in the database 21 of the storage device 20.

[0056] Step S605 When the unclassified travel route is added as a new route, the processing device 10 generates a new route ID for classifying the added new route, links the mesh set A related to the unclassified travel route, the operation data obtained on the unclassified travel route, the productivity index data calculated from the operation data, and the vehicle ID of the mining vehicle V that traveled the unclassified travel route to the new route ID, and records them in the storage device 20, then terminates the processing of Figure 6 and waits until the start of the next processing.

[0057] Step S606 If the minimum discrepancy is below the threshold, the processing device 10 classifies the unclassified travel route with the same route ID as the classified travel route (cycle ID) associated with the minimum discrepancy, links the classified route ID with mesh set A, operation data, productivity index, and vehicle ID, records them in the storage device 20, and temporarily terminates the processing of Figure 6 and waits until the start of the next processing.

[0058] -Comparison with conventional methods- Figure 7 is a comparison table between a mine management system based on a so-called node-link system and the mine management system 1 of this embodiment. In the so-called node-link system, the travel route of a mine vehicle is represented by nodes and links. If the distance between the mine vehicle's travel position information and a node on an existing route is smaller than the distance threshold, it is determined that the mine vehicle has passed that node. If the number of nodes determined to have passed through is greater than the match threshold, it is determined that the mine vehicle's travel route is the same as the existing route. However, the process required for this determination is complex, requiring distance calculations for position information at least as many times as the number of nodes to be compared. In addition, many parameters are required to set an existing route, including the position of each node, the number of nodes, the distance threshold, and the match threshold. If these parameters are not set appropriately, route determination may be incorrect. Furthermore, while positioning errors and deviations in the travel route of a mine vehicle can be addressed by adjusting the distance threshold, the aforementioned inclusions and detours cannot be detected, and additional discrimination conditions must be added to make such determinations.

[0059] In contrast, in this embodiment, the above-mentioned problems of the node-link method are solved by converting the position data of a driving route into a mesh set (a set of mesh IDs) and evaluating the degree of discrepancy between the mesh sets of unclassified driving routes and classified driving routes. Specifically, route classification requires only two calculations: calculating the degree of discrepancy (first difference set Δ1 or ratio R1) of mesh set B of classified driving routes relative to the union Σ, and calculating the degree of discrepancy (second difference set Δ2 or ratio R2) of mesh set A of unclassified driving routes relative to the union Σ. Furthermore, the only parameters suitable for route classification are the mesh size and thresholds S1 and S2 for evaluating the discrepancy. Deviations in driving routes due to GNSS positioning errors, such as variations in road surface conditions and driving skills, and avoidance of rough roads and other vehicles, can be easily addressed by adjusting the mesh size. Furthermore, the route classification algorithm of this embodiment evaluates the degree of discrepancy between routes, allowing for the aforementioned identification of inclusions and detours as separate routes from classified routes.

[0060] For example, if an unclassified travel route includes a "detour," the unclassified travel route deviates from the classified route midway, even if the start and end points are the same as those of the classified travel route. In the case of a detour, mesh sets A and B of the unclassified travel route and the classified travel route have a relationship like that shown in the Venn diagram of type c in Figure 5, so the second difference set Δ2 (or ratio R2) is greater than threshold S2 and the first difference set Δ1 (or ratio R1) is less than threshold S1. In this case, because the first difference set Δ1 (or ratio R1) is less than threshold S1 but the second difference set Δ2 (or ratio R2) is greater than threshold S2, the processing device 10 distinguishes the two travel routes related to mesh sets A and B as separate routes. If necessary, rather than simply distinguishing them as separate routes, the fact that the travel route included a "detour" may be recorded as additional information to the cycle ID.

[0061] Furthermore, if an unclassified travel route is a route that is "included" in another travel route, the unclassified travel route will entirely match a portion of a classified route. In the case of inclusion, the mesh sets A and B of the unclassified travel route and the classified travel route have a relationship like the Venn diagram shown in type d of Figure 5, so the first difference set Δ1 (or ratio R1) is zero and the second difference set Δ2 (or ratio R2) is greater than the threshold value S2. In this case, the first difference set Δ1 (or ratio R1) is less than or equal to the threshold value S1, but the second difference set Δ2 (or ratio R2) is greater than the threshold value S2, so the processing device 10 distinguishes the two travel routes related to mesh sets A and B as separate routes. If necessary, rather than simply distinguishing them as separate routes, the fact that they are "included" may be recorded as additional information in the cycle ID.

[0062] - Productivity index aggregation function - As described above, the storage device 20 (database 22) records the control parameters (engine idle speed, maximum speed, engine response) applied to the travel control of the mining vehicle V for each travel route (cycle ID). The processing device 10 references data related to multiple classified travel routes (cycle IDs) with the same route ID from the storage device 20, generates analytical data of productivity indexes calculated based on the operation data of each cycle ID for each control parameter, and outputs the analytical data for each control parameter to the display terminal device 30. In this case, the higher the travel frequency of a route ID, the greater the impact its productivity has on the overall productivity of the mining site S. Therefore, it is preferable that the processing device 10 weights the operation data according to the number of data points (travel frequency) for the route ID and calculates the weighted average of the aggregated data to calculate the analytical data. An example of this process will be described using Figure 8.

[0063] 8 is an example of a block diagram of the processing device 10 relating to the function of aggregating productivity indices for each route. In FIG. 8, the productivity indices aggregating function of the processing device 10 is represented by blocks 14 and 15.

[0064] In block 14, the processing device 10 refers to the data of all (or more than a set number of) classified driving routes (cycle IDs) accumulated in the database 22 during an evaluation period set by the user, for example, on the display terminal device 30, and extracts, as evaluation route IDs, route IDs whose driving frequency during the evaluation period is higher than a predetermined frequency threshold (i.e., the number of data items during the evaluation period is greater than a predetermined number).

[0065] In block 15, the processing device 10 reads data on each productivity index for each cycle ID of the extracted evaluation path ID from the database 22, and tally up the data on the productivity index for each evaluation path ID.

[0066] The frequency threshold used in the processing of block 14 is a value set by the user on the display terminal device 30, for example, and is a condition set to reduce variations in the calculation results of the productivity index due to, for example, the driving skill of the driver of the mining vehicle V and other conditions (e.g., waiting time due to cooperation with other vehicles, excavators, etc.). Therefore, it is desirable to set the frequency threshold to a value so that even if the extracted route IDs include several peculiar cycles (cycles significantly affected by waiting in line at the loading dock or traffic congestion), route IDs with a sufficient number of data points are extracted so that the impact on the aggregated results is below a certain level. By evaluating route IDs with particularly high driving frequencies, it is possible to easily understand the overall productivity evaluation trend of the mining site S.

[0067] -Control parameter evaluation procedure- FIG. 9 is a flowchart showing an example of a procedure for presenting recommended control parameters based on the tabulation results of productivity indices.

[0068] When the processing device 10 receives a request signal from the display terminal device 30 in response to a user's operation regarding a comparison of productivity based on control parameters, the processing device 10 executes the process of the flowchart in FIG.

[0069] Step S901 Upon receiving a request signal from the display terminal device 30, the processing device 10 selects an evaluation route during the evaluation period set by the user and transmits it to the display terminal device 30. For example, the processing device 10 calculates the driving frequency of each route ID during the evaluation period, sorts the route IDs in descending order of driving frequency, and displays these route IDs as candidates for evaluation route IDs in bar graph format together with a frequency threshold on the display terminal device 30. The selected route IDs may also be displayed in a parade diagram.

[0070] Step S902 When one or more evaluation route IDs are selected from the candidates displayed on the display terminal device 30, the processing device 10 aggregates productivity index data for each control parameter for the evaluation route ID transmitted from the display terminal device 30, and generates analysis data by performing a weighted average according to the driving frequency of the route ID. For example, analysis data for standard parameters and other alternative parameters (parameter α, parameter β, ...) for the maximum engine speed, idle speed, and engine response are calculated. If multiple evaluation route IDs are specified, analysis data is calculated for each evaluation route ID in the same manner.

[0071] Step S903 After calculating the productivity index analysis data for each control parameter for the evaluation path ID, the processing device 10 compares the productivity index for each control parameter and identifies the control parameter with the best productivity index. The identification method may involve comparing productivity indexes specified on the display terminal device 30, or it may involve prioritizing productivity indexes and comparing the productivity indexes with the highest priority. As a result, if there is an alternative parameter that improves productivity more than the standard parameter (Y), the processing device 10 proceeds from step S903 to step S904; if there is not (N), the processing device 10 proceeds from step S903 to step S905.

[0072] Step S904 If there is an alternative parameter that improves productivity more than the standard parameter, the processing device 10 indicates that the alternative parameter that improves productivity the most (for example, parameter α) is the recommended parameter, sends comparison data of the productivity index for each parameter to the display terminal device 30, displays it as dashboard information, and ends the processing of the flowchart in Figure 9.

[0073] Step S905 If there are no alternative parameters that will improve productivity more than the standard parameters, the processing device 10 indicates that the standard parameters are recommended parameters, transmits comparison data of productivity indices for each parameter to the display terminal device 30, and displays it as dashboard information, and then ends the processing of the flowchart in Figure 9.

[0074] 9, it is assumed that the recommended parameters are presented to a user (for example, equipment maintenance worker P4), and that when changing the control parameters, the user gets into each mining vehicle V and sets the recommended parameters, but if the control parameters of the mining vehicles V can be changed remotely, recommended parameter data may be sent from the processing device 10 to each mining vehicle V, and the control parameters of the mining vehicles V may be changed without manual intervention by the user. Also, instead of setting the control parameters of all vehicles operating at the mining site S uniformly, it is also possible to determine recommended parameters for each route ID, for example, by the processing in FIG. 9, and set different control parameters for each route ID to the mining vehicles V.

[0075] -Display example- 10A and 10B show an example of an evaluation path selection screen that the processing device 10 causes the display terminal device 30 to display.

[0076] Fig. 10A is a diagram showing an example of a screen presenting candidates for evaluation route IDs. The screen of Fig. 10A is displayed on the display terminal device 30, for example, in the procedure of step S901 of Fig. 9. Fig. 10A shows an example in which a bar graph is displayed in which route IDs are arranged from left to right in order of frequency of travel during the evaluation period, together with the frequency threshold. Note that although Fig. 10A shows an example of a bar graph, it may also be displayed as a parade diagram.

[0077] This display allows the user to grasp at a glance how many route IDs are suitable as candidates for evaluation route IDs. In the example of Figure 10A, it can be seen that four route IDs exceed the frequency threshold, indicating a sufficient amount of data. Furthermore, by considering factors such as the degree of margin for the frequency threshold, it is possible to estimate whether the impact on productivity evaluation will be small even if a small number of abnormal values ​​are mixed in. In the example of Figure 10A, the leftmost route ID of the four route IDs that exceed the frequency threshold has a larger margin for the frequency threshold than the other three route IDs, and it is estimated that it will have the least impact if there are a similar number of abnormal values.

[0078] Fig. 10B is a diagram showing an example of a screen that visualizes a mesh set linked to an evaluation route ID. On the screen of Fig. 10B, for example, the trajectory of the route ID selected in Fig. 10A is displayed as a mesh. Although not shown in the figure, by displaying it overlaid with a map or satellite photo of the mining site S, the user can grasp at a glance where the route traveled within the mining site S. This is also useful as a reference when considering control parameters for other route IDs that are located in close proximity (for example, route IDs with different loading points but a common dumping point).

[0079] 11A to 11D show examples of display screens of analysis data that the processing device 10 causes the display terminal device 30 to display.

[0080] Fig. 11A is an example of a screen showing a bar graph of the driving frequency for each control parameter for a selected evaluation route ID. Fig. 11A shows an example of a bar graph that displays, from left to right, the driving frequency for each control parameter, i.e., the number of cycle IDs during the evaluation period, in descending order based on the data for each cycle ID for the selected evaluation route ID, along with a frequency threshold (which may be a value different from the frequency threshold in Fig. 10A). By displaying in this way, the user can at a glance grasp which control parameters have a sufficient number of data points and for which comparison is meaningful.

[0081] FIG. 11B is an example of a screen showing a comparison of productivity using control parameters for a selected evaluation route ID. The values ​​of each control parameter shown in FIG. 11B are representative values ​​(e.g., average or median) of the data for the cycle ID being aggregated. For example, if the productivity index shown in FIG. 11B is the amount of cargo transported per liter of fuel (T / L), it can be seen that, for the evaluation route ID, setting an alternative parameter (particularly parameter α) as the control parameter allows more cargo to be transported with the same amount of fuel consumed than setting the standard parameter. This type of display is not limited to the amount of cargo transported per liter of fuel (T / L), but can also be used for the amount of cargo transported per unit time (T / h). It is also possible to display a comparison of multiple productivity indexes using control parameters for the same evaluation route ID side by side on a single screen, allowing for easy viewing.

[0082] In the example of Figure 11B, it can be seen that parameter α is recommended for the amount of cargo transported per liter of fuel (T / L), but by checking other productivity indices as well, it is possible to understand whether parameter α is recommended for all productivity indices in the evaluation route ID, or whether the recommended control parameters differ depending on the productivity indices.

[0083] Figure 11C is an example of a screen displaying histograms of the travel frequency (number of cycle IDs) for the standard parameters and parameter α for the same productivity index for a selected evaluation route ID. The histogram indicated by the dotted line represents the standard parameter data, and the histogram indicated by the solid line represents the parameter α data. The horizontal axis of Figure 11C represents a specified productivity index, such as the cargo transport volume per liter of fuel (T / L). In the example of Figure 11C, both the standard parameter data and the alternative parameter data are close to normal distribution, suggesting small variance and little influence from outliers. If a certain number of data points for extremely poor transport volume (T / L) are identified for the standard parameters in Figure 11C, even if the standard parameters appear unfavorable in Figure 11B, it can be understood that this may be due to irregular data. Taking this into consideration, the control parameters can be more appropriately determined.

[0084] Figure 11D is an example of a screen showing the difference in productivity depending on control parameters for multiple routes. When multiple evaluation route IDs are selected, it is possible to see at a glance which control parameters (in the example of Figure 11D, whether standard parameters or parameter α should be applied) will increase productivity for each evaluation route ID, e.g., the amount of cargo transported per liter of fuel (T / L). In the example of Figure 11D, the dotted bar graph represents the data for the standard parameters, and the solid bar graph represents the data for parameter α. The example of Figure 11D shows the difference in productivity depending on control parameters for four route IDs. Selecting control parameters that increase productivity for the route IDs that are frequently traveled among these routes can lead to improvements in the productivity of the entire mine site S. Furthermore, making such a selection also allows one to understand how productivity may change for other route IDs.

[0085] -effect- As described above, in this embodiment, the position data of the travel route is converted into a mesh set, and the degree of mismatch between the unclassified travel route and the mesh set of classified travel routes is evaluated. This reduces the calculation required for route classification to just two calculations: the degree of mismatch calculation. The only parameters required for route classification are the mesh size and the thresholds S1 and S2 for evaluating the degree of mismatch. GNSS positioning errors and deviations in the travel path of the mining vehicle V can be addressed by adjusting the mesh size, without the need to set route determination points or distance thresholds for each point. Furthermore, as described above, travel routes related to "inclusion" and "detour" can be distinguished as separate routes from classified routes. Because there is no need to set route determination points for each classified route, even if the dumping site or loading site moves, there is no need to reset the route determination points or distance thresholds accordingly. Therefore, this embodiment allows the travel route of the mining vehicle V to be accurately and easily classified.

[0086] Furthermore, because travel routes can be classified with high accuracy, the number of data points (number of cycle IDs) for each route ID can also be calculated with high accuracy, and the value of the productivity index can be properly evaluated. Furthermore, because the difference in productivity due to control parameters can be calculated and displayed for each route ID, this contributes to optimizing the setting of control parameters for each route ID and the user's judgment. In this case, because the number of data points for each route ID can be calculated with high accuracy, it is possible to identify route IDs with truly high travel frequencies and select control parameters that will increase productivity for travel routes with high travel frequencies, thereby easily improving the overall productivity of the mine site S.

[0087] (Second embodiment) A second embodiment of the present invention will be described with reference to FIGS.

[0088] This embodiment differs from the first embodiment in the content of the analysis after route classification, in which productivity is compared between mining vehicles V traveling the same route. Specifically, the processing device 10 references multiple data related to travel routes with the same route ID from the storage device 20 (database 22), generates analysis data by comparing productivity index data calculated based on operation data for each vehicle ID, and outputs the analysis data to the display terminal device 30. This makes it possible to extract deteriorated vehicles, etc. The route classification process is the same as in the first embodiment, and a description thereof will be omitted.

[0089] FIG. 12 is a flowchart showing an example of a procedure for determining a deteriorated vehicle.

[0090] When the processing device 10 receives a request signal from the display terminal device 30 in response to a user's operation regarding a comparison of productivity based on control parameters, the processing device 10 executes the process of the flowchart in FIG.

[0091] Step S1201 Step S1201 is the same as step S901 in FIG. 9 . That is, upon receiving a request signal from the display terminal device 30, the processing device 10 selects an evaluation route during the evaluation period set by the user and transmits it to the display terminal device 30. For example, the processing device 10 calculates the travel frequency of each route ID during the evaluation period, sorts the route IDs in descending order of travel frequency, and displays these route IDs as candidates for evaluation route IDs in bar graph format along with a frequency threshold on the display terminal device 30. The display is not limited to bar graph format and may be in other display formats. The selected evaluation route may also be displayed as a Pareto chart. The evaluation route ID is displayed in a manner that allows the route to be identified (for example, a straight line) on a map showing the area where the mining vehicle operates. Furthermore, when displaying multiple evaluation route IDs, routes with high and low travel frequencies may be distinguished by color, such as red or blue, or by line thickness.

[0092] Step S1202 When an evaluation route ID (one or more) and a productivity index to be evaluated are selected from the candidates displayed on the display terminal device 30, the processing device 10 calculates the selected productivity index data for each vehicle ID that traveled along the evaluation route ID for the evaluation route ID transmitted from the display terminal device 30. The calculated productivity index value can be a weighted average value according to the travel frequency of the route ID, in the same manner as in the first embodiment. For example, by selecting the amount of cargo transported per liter of fuel (T / L) or fuel efficiency (L / km) as the productivity index, the deterioration state of the powertrain (engine, generator, inverter, motor, etc.) of the mining vehicle V can be estimated. When multiple evaluation route IDs (at least two or more) are selected, a comparison result of each productivity index may be displayed.

[0093] Step S1203 After calculating the productivity index for each vehicle ID, the processing device 10 compares the selected productivity index data with a productivity threshold for each vehicle ID to determine whether the productivity is equal to or greater than the productivity threshold. The productivity threshold can be determined from the variance σ (e.g., 2-3σ) of the productivity indexes calculated for multiple vehicle IDs over multiple periods in the past.

[0094] Step S1204 As a result of the comparison with the productivity threshold, the processing device 10 determines that a vehicle ID whose productivity is less than the productivity threshold is a deteriorated vehicle, and causes the display terminal device 30 to display analysis data in a format that allows the productivity index for the evaluation route ID to be compared with other vehicle IDs, and presents this to a user (e.g., equipment maintenance worker P4), thereby completing the processing of the flowchart in Fig. 12. When comparing the analysis data of deteriorated vehicles, the order in which the productivity index values ​​are displayed can be arbitrarily changed based on a specified index from among multiple indexes included in the productivity index.

[0095] Step S1205 As a result of the comparison with the productivity threshold, the processing device 10 determines that the vehicle IDs whose productivity is equal to or greater than the productivity threshold are normal vehicles, and causes the display terminal device 30 to display analysis data that represents the productivity index for the evaluation route ID in a format that allows comparison with other vehicle IDs, and presents this to the user (e.g., equipment maintenance worker P4), thereby completing the processing of the flowchart in Fig. 12. When comparing the analysis data of normal vehicles, the order in which the productivity index values ​​are displayed can be arbitrarily changed based on a specified index from among multiple indexes included in the productivity index.

[0096] 13A and 13B show examples of screens of analysis data of the deterioration state of the vehicle that the processing device 10 causes the display terminal device 30 to display.

[0097] Fig. 13A is a diagram showing an example of a screen displaying the productivity of each vehicle ID that traveled a selected route ID. In the example of Fig. 13A, a representative value (e.g., an average value) of the productivity index of each vehicle ID on one evaluation route ID is displayed together with a productivity threshold, and the vehicle IDs are displayed from left to right in order of decreasing productivity. From this display, it can be seen that the mining vehicles V with vehicle IDs (v1-v3) are normal vehicles with productivity equal to or greater than the productivity threshold, and the mining vehicle V with vehicle ID (v4) is a deteriorated vehicle with productivity below the productivity threshold.

[0098] FIG. 13B shows a histogram of predetermined operational data for each cycle in the evaluation route. The predetermined operational data is, for example, operational data selected by the user on the display terminal device 30 to determine the cause of productivity decline. For example, the predetermined operational data may be one or more items of operational data, such as fuel consumption per cycle of the evaluation route ID, cargo transport volume, and required time. If multiple operational data are selected, it is recommended that multiple displays of FIG. 13B be displayed side by side. In FIG. 13B, the histogram indicated by the dotted line represents data for normal vehicles (v1, v2, v3), and the histogram indicated by the solid line represents data for a deteriorated vehicle (v4). If FIG. 13B shows fuel consumption per cycle, it can be seen that the deteriorated vehicle (v4) consumes more fuel overall than the normal vehicles (v1, v2, v3). In this case, for example, an abnormality in the powertrain of the deteriorated vehicle (v4) is suspected.

[0099] According to this embodiment, a user (e.g., equipment maintenance personnel P4) can easily identify degraded vehicles with reduced productivity. Also, by dividing vehicles into normal and degraded vehicles and comparing the trends in the operational data of degraded vehicles with that of normal vehicles, it becomes easier to estimate the factors behind the decline in productivity of degraded vehicles, and for example, it is possible to improve the efficiency of maintenance work on degraded vehicles by equipment maintenance personnel P4.

[0100] (Third embodiment) A third embodiment of the present invention will be described with reference to Figures 14 to 16. In this embodiment, a method for further improving the accuracy of route classification and reducing the calculation load will be described.

[0101] Fig. 14 is a conceptual diagram for explaining an omnidirectional mesh. In Fig. 14, mesh set B of classified travel routes is represented by one mesh for simplicity. In this embodiment, route classification is made more robust by adding omnidirectional mesh B', which is a set of meshes (meshes B1 to B8 in Fig. 14) that are adjacent to mesh set B of classified travel routes that have been passed by a mining vehicle V and that surround mesh set B vertically, horizontally, and diagonally, to mesh set B of classified travel routes.

[0102] 15 is a schematic diagram illustrating an example of route classification using an omnidirectional mesh. As in the first and second embodiments, B is a mesh set of classified travel routes, and A is a cycle set. In this embodiment, a new omnidirectional mesh set B' of mesh set B is recorded in the database 22 of the storage device 20. During route classification processing, the ratio R2' (R2' = (Σ' - (B∪B') / Σ') of the difference set Δ2' (Δ2' = Σ' - (B∪B')) obtained by subtracting B∪B' from the union Σ' (= B∪B'∪A) of mesh sets A, B and omnidirectional mesh set B' is calculated. The difference set Δ2' or ratio R2' represents the degree of discrepancy between mesh set A of unclassified travel routes and the union obtained by adding omnidirectional mesh set B' to mesh set B of classified travel routes. In this embodiment, Δ2' or R2' is used instead of Δ2 or R2 in the first and second embodiments, and it is determined whether Δ2' or R2' is smaller than threshold value S2.

[0103] This effectively prevents travel routes that should be classified as the same route ID from being determined to be different routes, and prevents the number of route IDs from increasing more than necessary during the evaluation period. At the same time, the number of data points with the same route ID increases. This makes it possible to determine control parameters and deteriorated vehicles based on a larger amount of data.

[0104] (Fourth embodiment) 16 is a flowchart showing an example of the procedure for deleting route IDs with low travel frequencies by a processing device constituting a mine management system according to a fourth embodiment of the present invention. In this embodiment, the processing device 10 deletes data for route IDs for which the number of data items recorded during a preset evaluation period is less than a preset number from the storage device 20 (database 22). Except for this point, the other processes executed in this embodiment are the same as those in any of the first to third embodiments.

[0105] The processing device 10 executes the process of Fig. 16, for example, when a preset period has elapsed since the previous execution of the process of Fig. 16. However, the process of Fig. 16 may be executed sequentially, or may be executed when the route IDs of the classified travel routes reach a preset number.

[0106] Step S1601 When the processing of FIG. 16 is started, the processing device 10 first reads from the storage device 20 a predetermined evaluation period (for example, the past three months) for calculating the travel frequency of each route ID.

[0107] Step S1602 After reading the evaluation period, the processing device 10 calculates the frequency of travel based on the number of cycle IDs accumulated during the evaluation period for each route ID.

[0108] Step S1603 After calculating the travel frequency of each route ID, the processing device 10 determines whether the travel frequency is less than a preset value (threshold value). For route IDs whose travel frequency is equal to or greater than the set value, the processing of Fig. 16 ends here. For route IDs whose travel frequency is less than the set value, the procedure proceeds to step S1604.

[0109] Step S1604 For route IDs whose travel frequency is less than a set value, the processing device 10 deletes the route ID from the storage device 20 (database 22) and ends the processing of Figure 16. The process of deleting a route ID is not limited to erasing the data, but may also involve adding an unusable flag to the data of the route ID, specifying that the route ID cannot be used for route classification. Route IDs with an unusable flag attached are excluded from the usage data when the route classification process (Figure 6) is executed.

[0110] According to this embodiment, in the route classification process, travel routes with low travel frequency are excluded from classification candidates, and the number of travel routes that require inconsistency determination is reduced, thereby reducing the calculation load on the processing device 10. [Explanation of symbols]

[0111] 1...mine management system, 10...processing device, 20...storage device, 30...display terminal device, A, B...mesh set, D...soil dumping site (end point), O...soil dumping site (start point), S1, S2...threshold value, V...mine vehicle, Δ1...first difference set, Δ2...second difference set, Σ...union set

Claims

1. a processing device that generates a mesh set represented by IDs of meshes that divide the ground surface at equal intervals for a travel route starting from the location where the mining vehicle has dumped soil and ending at the location where the mining vehicle will next dump soil, based on the position data and operation data of the mining vehicle, and classifies the route IDs based on the mesh set; a storage device that stores and accumulates the mesh set and the operation data in association with the travel route generated by the processing device; a display terminal device that transmits and receives data to and from the processing device and displays the data received from the processing device; In a mine management system comprising: The processing device includes: For a mesh set A of unclassified travel routes that is an unclassified travel route and a mesh set B of classified travel routes that is a classified travel route, a union that is the logical sum of the mesh set A and the mesh set B, a first difference set that is the logical difference between the union and the mesh set A, and a second difference set that is the logical difference between the union and the mesh set B are calculated; If the sizes of both the first difference set and the second difference set are equal to or smaller than respective preset thresholds, the unclassified travel route is classified into a route ID of the classified travel route, and the mesh set A and the operation data related to the unclassified travel route are linked to the route ID and recorded in the storage device; If at least one of the sizes of the first difference set and the second difference set is greater than the threshold, a new route ID is generated, and the mesh set A and the operation data related to the unclassified travel route are linked to the new route ID and recorded in the storage device. A mine management system characterized by:

2. The mine management system according to claim 1, The processing device distinguishes the route from the classified route when the size of the second difference set is greater than the threshold and the size of the first difference set is equal to or less than the threshold.

3. The mine management system according to claim 1, The mine management system is characterized in that the processing device distinguishes the route from the classified route when the size of the first difference set is zero and the size of the second difference set is greater than the threshold.

4. The mine management system according to claim 1, The storage device stores control parameters applied to travel control of the mining vehicle for each travel route, The processing device references data relating to a plurality of travel routes having the same route ID from the storage device, aggregates data of productivity indexes calculated based on the operation data for each of the control parameters, generates analysis data, and outputs the analysis data for each of the control parameters to the display terminal device. A mine management system characterized by:

5. 5. The mine management system according to claim 4, The mine management system is characterized in that the processing device calculates the analysis data by taking a weighted average of the aggregated values ​​of the productivity index depending on the number of data points of the route ID.

6. The mine management system according to claim 1, The processing device refers to a plurality of data relating to travel routes having the same route ID from the storage device, generates analysis data by comparing productivity index data calculated based on the operation data for each of the mining vehicles, and outputs the analysis data to the display terminal device. A mine management system characterized by:

7. 7. The mine management system according to claim 6, wherein the route IDs are output in a display order based on an arbitrarily designated productivity index from among the productivity indexes included in the analysis data.

8. The mine management system according to claim 1, The mine management system is characterized in that the processing device deletes data of route IDs for which the number of data recorded during a predetermined evaluation period is less than a predetermined number from the storage device.

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