CN115840627B - Mine car task scheduling method and device based on Internet of vehicles - Google Patents
Mine car task scheduling method and device based on Internet of vehicles Download PDFInfo
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Abstract
The application relates to a mine car task scheduling method, device and storage medium based on the Internet of vehicles. The method comprises the following steps: the existing fault data of the mine car are stored in a system database in a manual input mode; the fault data of the mine car is derived from a fault maintenance record table from the service of the mine car; the method comprises the steps of operating years of the mine car, maintenance times of an engine, maintenance times of a mine car wheel set and maintenance times of a braking system; meanwhile, pre-storing vibration threshold signals of the mining vehicle wheel pair in a normal state and an abnormal state in a system database; calculating fault indexes of each mine car, classifying each mine car according to the fault indexes, determining classification results, acquiring scheduling tasks, calculating task difficulties of the scheduling tasks, determining mine cars to be scheduled according to classification results and task difficulties, and further controlling the mine cars to run. And simultaneously, monitoring wheel set vibration signals in the process of executing tasks of the mine car in real time, comparing the wheel set vibration signals with vibration threshold signals, and if abnormality is found, timely processing. Therefore, the purpose of improving task scheduling efficiency by scheduling according to the fault indexes of the mine car is achieved.
Description
Technical Field
The application relates to the technical field of automatic driving, in particular to a mine car task scheduling method and device based on the Internet of vehicles.
Background
The conventional mining area task scheduling has the following problems: 1. the mine is large in area and outdoor, is easily influenced by external factors such as weather change, up-down gradient, vehicle energy consumption and the like, and is fully random in scheduling due to dynamic change of the state of a driver; 2. when the mine car and the electric shovel are in fault, traffic jam or task scheduling delay is easily caused; 3. scheduling involves multiple participating subjects, such as mine cars, electric shovels; scheduling requires consideration of a number of factors, such as the distance of the mine car from the electric shovel, the electric shovel waiting time, etc.
In year 2020, the eight committee jointly issues guidance on accelerating intelligent development of coal mines, and in year 2025, the open pit coal mine realizes intelligent continuous operation and unmanned transportation. Mining area operation mainly faces the problems of difficult job recruitment, high job cost, extreme operation environment, frequent safety accidents and the like. The selling price of the manned mine car with the load of 100 tons is 80 ten thousand, 2-3 drivers are equipped, and the salary is about 30 ten thousand yuan/year. The cost of the automatic driving ore card transformed into the automatic driving ore card through the wire control transformation is about 60 ten thousand yuan by additionally installing the sensor and the computing unit, so that the automatic driving ore card can realize the balance of both earnings and earnings in 2 years and realize the earning in 3 years compared with the traditional manned ore card. Therefore, the problem of difficult work and personnel in mining areas is solved by adopting the intelligent driving system of the Internet of vehicles, and the intelligent driving system has been adopted by some mining areas and has achieved some effects.
As industrial mechanical equipment, with the growth of years, the engine, the mine car wheel set and the braking system are inevitably subjected to faults in the use process, for example, the mine car is required to bear the influence and restriction of gravity, friction and the like in the running process, the running safety of the mine car is directly influenced by the abrasion degree, and once the mine car is faulty or damaged, the mine car is difficult to work. However, the operation and maintenance of mine cars still use the traditional maintenance mechanism based on pre-preventive protection and post-fault maintenance, so that faults are difficult to find in early stage, and the dispatching production efficiency of the whole mining area is further affected. Therefore, one of the guarantees of dispatching tasks is that the mine car does not fail, and the mine car failure index is not used as a dispatching index for dispatching at present. In view of the foregoing, it is desirable to provide a system that can perform scheduling according to mine car failure indexes, thereby achieving the purpose of improving task scheduling efficiency.
Disclosure of Invention
Based on the task scheduling method, the application provides a mine car task scheduling method based on the Internet of vehicles.
A mine car task scheduling method based on the internet of vehicles, the method comprising:
step one: the existing fault data of the mine car are stored in a system database in a manual input mode; the fault data of the mine car is derived from a fault maintenance record table from the service of the mine car, and comprises the operation years of the mine car, the maintenance times of an engine, the maintenance times of a mine car wheel set and the maintenance times of a braking system; meanwhile, pre-storing vibration threshold signals of the mining vehicle wheel pair in a normal state and an abnormal state in a system database; the method comprises the steps of carrying out a first treatment on the surface of the
Step two: calculating fault indexes of each mine car, classifying each mine car according to the fault indexes, and determining classification results;
step three: acquiring a dispatching task, calculating task difficulty of the dispatching task, determining a mine car to be dispatched according to a grading result and the task difficulty, and further controlling the mine car to run;
step four: and monitoring wheel set vibration signals in the process of executing tasks of the mine car in real time, comparing the wheel set vibration signals with vibration threshold signals, and if abnormality is found, timely processing.
A mine car task scheduling device, the device comprising:
the data input module is used for storing the existing fault data of the mine car in a system database in a manual input mode; the fault data of the mine car is derived from a fault maintenance record table from the service of the mine car, and comprises the operation years of the mine car, the maintenance times of an engine, the maintenance times of a mine car wheel set and the maintenance times of a braking system; meanwhile, pre-storing vibration threshold signals of the mining vehicle wheel pair in a normal state and an abnormal state in a system database;
the calculation module is used for calculating the fault index of each mine car, classifying each mine car according to the fault index and determining the classification result;
the scheduling module is used for acquiring scheduling tasks, calculating task difficulty of the scheduling tasks, determining mine cars to be scheduled according to classification results and the task difficulty, and further controlling the mine cars to run;
the monitoring module monitors wheel set vibration signals in the process of executing tasks of the mine car in real time, compares the wheel set vibration signals with vibration threshold signals, and processes the wheel set vibration signals in time if abnormality is found;
and after the dispatching task is finished, updating a fault database according to fault data in the task execution process.
According to the mine car task scheduling method and device based on the Internet of vehicles, the existing mine car fault data are stored in the system database in a manual input mode; wherein the fault data of the mine car is derived from a fault maintenance record table from the service of the mine car. Calculating fault indexes of each mine car, classifying each mine car according to the fault indexes, determining classification results, acquiring scheduling tasks, calculating task difficulties of the scheduling tasks, determining mine cars to be scheduled according to classification results and task difficulties, and further controlling the mine cars to run. Therefore, the suitable mine car can be selected according to the car condition and task difficulty of the mine car before dispatching, and further real-time fault data of the mine car can be obtained by monitoring the vibration signals of the wheel sets in real time, and the fault data of the system database is updated according to the real-time fault data; the inconvenience caused by mine car faults is reduced, and the driving safety of the unmanned mine car and the timeliness of task completion are improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a task scheduling method for a mine car based on the Internet of vehicles, which is provided by an embodiment of the application;
FIG. 2 is a diagram of a mine car task scheduling device employing the method of the present application based on the Internet of vehicles, which is provided by the embodiment of the present application.
Detailed Description
The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
The mine car transportation driving control method provided by the application, as shown in figure 1, comprises the following steps: step 101: the existing fault data of the mine car are stored in a system database in a manual input mode; in step 101, mine car fault data is derived from a fault maintenance log from the time the mine car is serviced. Meanwhile, pre-storing vibration threshold signals of the mining vehicle wheel pair in a normal state and an abnormal state in a system database. In order to quickly and accurately realize fault early warning of the mine car, information support such as historical fault data, current running state of the mine car and the like is needed.
Step 102: and calculating fault indexes of each mine car, classifying each mine car according to the fault indexes, and determining classification results.
Specifically, the steady operation state of the unmanned mine car task schedule may become an abnormal operation state under the influence of some uncertainty factor. When the mine car is in a steady state, it can respond steadily to various uncertainty factors. Such as extreme weather, routine maintenance and the like, and pre-judging the normal load of the mine car, thereby providing a basis for the whole mine dispatching system. In the process of executing tasks, the mine car breaks down to occupy the road and breaks down, so that the dispatching operation and the ore drawing efficiency are seriously affected. The problems of welding between an engine, a mine car wheel set, a braking system, a side dump type mine car frame and a car hopper and the like are common fault problems which seriously affect the efficiency in actual production.
The application selects the running years of the mine car, the maintenance times of the engine and the maintenance times of the mine car wheel pair and the maintenance times of the braking system as reference indexes. The operation life of the equipment is an important reference of equipment fault indexes, and under the condition of lack of maintenance, the equipment fault indexes with longer operation time are increased; the working conditions on the mine are bad, the load is large, the driving road is bent steeply, the failure frequency of the engine is high, the more the failure times are, the more the possibility of engine dysfunction is; the electric wheel is used as a transmission, walking and main bearing mechanism of the mine car, and is subjected to huge car body load and complex impact from a road surface in the running operation process of the mine car, so that the mine car is most likely to be broken down; the complete function of the braking system is a key for ensuring the mine car to run in severe mines. Therefore, the four indexes are selected, the running years of the mine car, the maintenance times of the engine, the maintenance times of the mine car wheel set and the maintenance times of the brake system are respectively judged, and the mine car is classified into 3 stages according to the four indexes. The mine car runs for more than five years, the maintenance times exceed 3 times, the mine car runs for more than five years, the maintenance times are less than 3 times, the mine car is integrated into a 2-level data base, and the rest mine cars are integrated into a 1-level data base as a first choice for coping with severe environments. The maintenance times are the sum of the engine maintenance times, the maintenance times of the mine car wheel pair and the maintenance times of the braking system.
Step 103: and acquiring a dispatching task, calculating the task difficulty of the dispatching task, determining a mine car to be dispatched according to the classification result and the task difficulty, and further controlling the mine car to run.
Step 104: and monitoring wheel set vibration signals in the process of executing tasks of the mine car in real time, comparing the wheel set vibration signals with vibration threshold signals, and if abnormality is found and timely processed, judging that the vibration threshold signals are vibration signals in the vertical direction of the mine car.
Further, the task difficulty may be set to two different levels depending on weather conditions and the distance the task is scheduled. The mining method has the advantages that the influence of rain and snow weather on the mining area road is large, so that the difficulty level of a task is influenced, and the mine car with good dispatching conditions is favorable for the smooth completion of the task. According to the method, rainy and snowy weather is used as a first index for measuring task difficulty, mining vehicles in a level 1 database, such as a level 1 database mining vehicle, are scheduled preferentially when the rainy and snowy weather is met, and then scheduling of a level 2 database is performed. And when weather is good, selecting and dispatching mine cars in databases of different levels according to the distance of tasks to be dispatched and road condition information. According to the distance of the task to be scheduled and road condition information, selecting and scheduling mine cars in databases of different levels specifically comprises the following steps: firstly, considering the road condition risk level, when the road condition risk level is high, preferentially scheduling the mine cars in the level 1 database, and failing to schedule the mine cars in the level 3 database; when the road condition danger level is middle, scheduling the mine car according to the sequence of the level 1, level 2 and level 3 databases; when the road condition risk level is low, when the distances between all mine cars and the task points exceed a preset threshold value, adopting a scheduling sequence of a 2-level database and a 1-level database; and when the threshold value is smaller than the threshold value, dispatching the mine car of the 3-level database. Wherein the above threshold can be specifically set by a person skilled in the art depending on the size of the mine.
The road condition risk level can be divided according to whether the mine car has a curve, a ramp, a barrier, a one-way road and the like on the way of reaching a task point, if the road condition risk level containing all abnormal conditions is high, the road condition risk level containing two or three abnormal conditions is low, and the road condition risk level containing no or single abnormal condition is low.
By means of the dispatching, the dispatching efficiency of the whole mining area is improved on the basis of the dispatching safety of the mine cars.
It should be understood that, although the steps in the flowchart of fig. 2 are shown in sequence as indicated by the arrows, the steps are not necessarily performed in sequence as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least a portion of the steps in fig. 2 may include a plurality of steps or stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages is not necessarily sequential, but may be performed in rotation or alternatively with at least a portion of the steps or stages in other steps or other steps.
In one embodiment, as shown in FIG. 2, a mine car task scheduler is provided, the apparatus comprising:
the data input module is used for storing the existing fault data of the mine car in a system database in a manual input mode; the method comprises the steps of calculating fault indexes of each mine car, classifying each mine car according to the fault indexes, and determining classification results;
the calculation module is used for calculating the fault index of each mine car, classifying each mine car according to the fault index and determining the classification result;
the scheduling module is used for acquiring scheduling tasks, calculating task difficulty of the scheduling tasks, determining mine cars to be scheduled according to classification results and the task difficulty, and further controlling the mine cars to run;
the monitoring module monitors wheel set vibration signals in the process of executing tasks of the mine car in real time, compares the wheel set vibration signals with vibration threshold signals, and if abnormality is found and timely processed, the vibration threshold signals are vibration signals in the vertical direction of the mine car.
Further, after the dispatching task is finished, the fault data in the system database is updated according to the fault data in the task execution process.
In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored which, when executed by a processor, carries out the steps of the method embodiments described above.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, or the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory. By way of illustration, and not limitation, RAM can be in the form of a variety of forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), and the like.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples illustrate only a few embodiments of the application, which are described in detail and are not to be construed as limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of protection of the present application is to be determined by the appended claims.
Claims (5)
1. A mine car task scheduling method based on the internet of vehicles, the method comprising:
step one: the existing fault data of the mine car are stored in a system database in a manual input mode; the fault data of the mine car is derived from a fault maintenance record table from the service of the mine car, and comprises the operation years of the mine car, the maintenance times of an engine, the maintenance times of a mine car wheel set and the maintenance times of a braking system; meanwhile, pre-storing vibration threshold signals of the mining vehicle wheel pair in a normal state and an abnormal state in a system database;
step two: calculating fault indexes of each mine car, classifying each mine car according to the fault indexes, and determining classification results; judging the running years of the mine car, the maintenance times of the engine, the maintenance times of the mine car wheel pair and the maintenance times of the braking system respectively, and classifying the mine car into 3 grades according to the four indexes; the mine car runs for more than five years, the maintenance times exceeds 3 times, the mine car is integrated into a 3-level database, the mine car runs for more than five years, the maintenance times is less than 3 times, the mine car is integrated into a 2-level database, the other mine cars are integrated into a 1-level database, and the maintenance times are the sum of the engine maintenance times, the mine car wheel pair maintenance times and the brake system maintenance times;
step three: acquiring a dispatching task, calculating task difficulty of the dispatching task, determining a mine car to be dispatched according to a mine car grading result and the task difficulty, and further controlling the mine car to run; setting two levels of task difficulty according to weather conditions and task scheduling distances, preferentially scheduling mine cars in a level 1 database in rainy and snowy weather, and then scheduling a level 2 database; when weather is good, selecting and dispatching mine cars in databases of different levels according to the distance of tasks to be dispatched and road condition information;
step four: monitoring wheel set vibration signals in the process of executing tasks of the mine car in real time, comparing the wheel set vibration signals with vibration threshold signals, and if abnormality is found, timely processing;
according to the distance of the task to be scheduled and road condition information, selecting and scheduling mine cars in databases of different levels specifically comprises the following steps:
firstly, considering the road condition risk level, when the road condition risk level is high, preferentially scheduling the mine cars in the level 1 database, and failing to schedule the mine cars in the level 3 database; when the road condition danger level is middle, scheduling the mine car according to the sequence of the level 1, level 2 and level 3 databases; when the road condition risk level is low, when the distances between all mine cars and the task points exceed a preset threshold value, adopting a scheduling sequence of a 2-level database and a 1-level database; and when the threshold value is smaller than the threshold value, dispatching the mine car of the 3-level database.
2. The car networking based mine car task scheduling method according to claim 1, wherein after the task scheduling is finished, fault data in the system database is updated according to fault data in the task execution process.
3. The method for dispatching the mine car task based on the internet of vehicles according to claim 1, wherein in the fourth step, the vibration threshold signal is a vibration signal of the mine car in the vertical direction.
4. A mine car task scheduling device based on the internet of vehicles for performing the mine car task scheduling method of any one of claims 1-3, the device comprising:
the data input module is used for storing the existing fault data of the mine car in a system database in a manual input mode; the fault data of the mine car is derived from a fault maintenance record table from the service of the mine car, and comprises the operation years of the mine car, the maintenance times of an engine, the maintenance times of a mine car wheel set and the maintenance times of a braking system; meanwhile, pre-storing vibration threshold signals of the mining vehicle wheel pair in a normal state and an abnormal state in a system database;
the calculation module is used for calculating the fault index of each mine car, classifying each mine car according to the fault index and determining the classification result; judging the running years of the mine car, the maintenance times of the engine, the maintenance times of the mine car wheel pair and the maintenance times of the braking system respectively, and classifying the mine car into 3 grades according to the four indexes; the mine car runs for more than five years, the maintenance times exceeds 3 times, the mine car is integrated into a 3-level database, the mine car runs for more than five years, the maintenance times is less than 3 times, the mine car is integrated into a 2-level database, the other mine cars are integrated into a 1-level database, and the maintenance times are the sum of the engine maintenance times, the mine car wheel pair maintenance times and the brake system maintenance times;
the scheduling module is used for acquiring scheduling tasks, calculating task difficulty of the scheduling tasks, setting two levels according to weather conditions and scheduling task distances, preferentially scheduling mine cars in a level 1 database in rainy and snowy weather, and then scheduling a level 2 database; otherwise, when the weather is good, selecting and dispatching the mine cars in the databases of different levels according to the distance of the tasks to be dispatched and the road condition information; according to the classification result and the task difficulty, determining the mine car to be dispatched, and further controlling the mine car to run, wherein the selecting and dispatching the mine cars in the databases of different levels according to the distance and road condition information of the task to be dispatched specifically comprises the following steps:
firstly, considering the road condition risk level, when the road condition risk level is high, preferentially scheduling the mine cars in the level 1 database, and failing to schedule the mine cars in the level 3 database; when the road condition danger level is middle, scheduling the mine car according to the sequence of the level 1, level 2 and level 3 databases; when the road condition risk level is low, when the distances between all mine cars and the task points exceed a preset threshold value, adopting a scheduling sequence of a 2-level database and a 1-level database; and when the threshold value is smaller than the threshold value, dispatching the mine car of the 3-level database.
5. The internet of vehicles-based mine car task scheduling device according to claim 4, wherein the fault database is updated according to fault data during task execution after the scheduled task is completed.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101510365A (en) * | 2009-03-03 | 2009-08-19 | 西安强军信息科技有限公司 | Method for optimizing and scheduling vehicle for flight ground safeguard |
| CN104346221A (en) * | 2013-08-02 | 2015-02-11 | 北京百度网讯科技有限公司 | Method and device for grading and dispatching management of server hardware equipment and server |
| CN111311129A (en) * | 2020-03-31 | 2020-06-19 | 广东电网有限责任公司 | Automatic work distribution method, system and computer equipment for power distribution network on-duty task allocation |
| CN111461539A (en) * | 2020-03-31 | 2020-07-28 | 广东电网有限责任公司 | Distribution network dispatching work task difficulty grading method and system and computer equipment |
| CN115456457A (en) * | 2022-09-29 | 2022-12-09 | 山东仝锐电气有限公司 | Coal mine vehicle scheduling method, system, equipment and storage medium |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090099720A1 (en) * | 2007-10-16 | 2009-04-16 | Elgali Mordechai | Monitoring the operation and maintenance of vehicles |
| US11442457B2 (en) * | 2018-11-28 | 2022-09-13 | International Business Machines Corporation | Navigation via predictive task scheduling interruption for autonomous vehicles |
-
2022
- 2022-12-19 CN CN202211631517.1A patent/CN115840627B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101510365A (en) * | 2009-03-03 | 2009-08-19 | 西安强军信息科技有限公司 | Method for optimizing and scheduling vehicle for flight ground safeguard |
| CN104346221A (en) * | 2013-08-02 | 2015-02-11 | 北京百度网讯科技有限公司 | Method and device for grading and dispatching management of server hardware equipment and server |
| CN111311129A (en) * | 2020-03-31 | 2020-06-19 | 广东电网有限责任公司 | Automatic work distribution method, system and computer equipment for power distribution network on-duty task allocation |
| CN111461539A (en) * | 2020-03-31 | 2020-07-28 | 广东电网有限责任公司 | Distribution network dispatching work task difficulty grading method and system and computer equipment |
| CN115456457A (en) * | 2022-09-29 | 2022-12-09 | 山东仝锐电气有限公司 | Coal mine vehicle scheduling method, system, equipment and storage medium |
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