CN111461568B - Method for evaluating performances of strip mine trucks - Google Patents
Method for evaluating performances of strip mine trucks Download PDFInfo
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Abstract
The invention discloses a method for evaluating the performance of a strip mine truck, which can obtain truck performance indexes such as truck yield, average energy consumption, operation stability, average efficiency, truck overspeed alarm, spinning wheel alarm, non-preheating alarm, acceleration and deceleration emergency alarm, bucket lifting and reversing alarm, parking brake alarm and the like by analyzing the state parameters of the truck and processing the state parameters, and comprehensively evaluate the performance, economy and operation level of a truck driver by the performance indexes.
Description
Technical Field
The invention belongs to the energy industry, and particularly relates to a method for evaluating the performance of a strip mine truck, which is suitable for the performance analysis of the strip mine truck, the economic analysis of the strip mine truck and the operation level analysis of a strip mine truck driver.
Background
With the advancement of industry 4.0, the open pit is required to scientifically evaluate the operation performance of important equipment, the open pit truck is an important equipment for influencing the production of the open pit, no scientific evaluation method exists at present, and how to utilize real-time state data of open pit truck equipment to scientifically evaluate the performance of the truck after processing treatment becomes a technical difficulty of the industry.
Disclosure of Invention
The invention aims to provide a method for evaluating the performance of a strip mine truck, which is characterized in that the real-time state parameters of the strip mine truck are processed and analyzed to obtain a strip mine truck performance evaluation model, so that the performance index of the strip mine truck can be calculated on line, and the performance analysis, the economic analysis and the on-line evaluation of the operation level of a truck driver are carried out on the truck.
In order to achieve the above purpose, the invention adopts the following technical scheme:
a method for evaluating the performance of a strip mine truck comprises the following steps:
1) Collecting real-time data of truck operation
Collecting real-time data of truck operation, including real-time data of truck GPS longitude KCJD, truck latitude KCWD, electric shovel GPS longitude DCJD, electric shovel latitude DCWD, truck speed KCSD, GPS speed GPSCS, truck lift bucket KCJD, engine speed FDJZS, parking brake ZCDD and generator net power JGL;
2) Processing real-time data
The real-time data of the secondary processing truck is used for obtaining truck yield CL, average energy consumption PJNH, operation stability CZPWX, average efficiency PJXL, total electric consumption ZHDL, total mileage ZLCS, accumulated acceleration LJJSD, total driving time ZJSJ, truck overspeed alarm, spinning wheel alarm, non-preheating alarm, acceleration and deceleration emergency alarm, lift bucket reversing alarm and parking brake alarm performance indexes;
3) Establishing a radar chart for evaluating truck performance
Carrying out radar chart analysis on truck performance indexes such as truck yield, average energy consumption, operation stability, average efficiency, safety index and the like obtained by secondary processing to obtain a truck performance evaluation system;
4) Evaluation of truck Performance and truck driver operating level
Real-time scoring is performed according to the truck performance radar chart, and the truck performance and the operation level of a driver are evaluated.
The invention is further improved in that in the step 2), the calculation formula of the performance index is as follows:
truck yield, calculated as follows:
yield = truck yield number x 220T
Wherein 220 is the truck full load;
average energy consumption, the formula of calculation is:
PJNH＝ZHDL÷ZLCS
the ZHDL is realized by accumulating JGL and calculated interval duration;
ZLCS is realized by KCSD and calculating interval duration in an accumulated way;
operational stability, the formula of calculation is:
CZPWX＝LJJSD÷ZJSSJ
wherein, LJJSD is realized by continuously accumulating the |KCSD_1-KCSD| in each calculation period, wherein KCSD_1 is KCSD 1 second before the calculation time; ZJSJ is realized by continuously accumulating the calculation period duration when KCSD >0 in each calculation period;
average efficiency, the calculation formula is:
PJXL＝ZJSSJ÷CL
the safety index is the sum of the alarm times of equipment such as truck overspeed alarm, spinning wheel alarm, non-preheating alarm, acceleration and deceleration emergency alarm, bucket lifting and reversing alarm, parking brake alarm and the like, and the lower the value is, the safer the value is;
(1) Overspeed alarm: alarming when KCSD is more than 32 km/h;
(2) Spinning wheel alarming: taking KCSD before the calculation time of 8 seconds, calculating the KCSD as KCSD_8, and alarming if KCSD_8>5 and the calculation time GPSCS=0;
(3) And (5) non-preheating alarm: starting timing when FDJZS rises from 0 to 700, and alarming if KCSD >0 in 5 minutes;
(4) Acceleration and deceleration emergency alarm: taking the KCSD before the calculation time of 1 second, calculating the KCSD as KCSD_1, and alarming if the calculation time is |KCSD_1-KCSD| > 5;
(5) And (5) bucket lifting reversing alarm: when KCJD=1, alarm if KCSD < -0.5 km/h;
(6) Number of parking brake errors: when zzd=1, alarm if |kcsd| > 0.
The invention has the following beneficial technical effects:
by analyzing the state parameters of the truck, the invention can obtain truck performance indexes such as truck yield, average energy consumption, operation stability, average efficiency, truck overspeed alarm, spinning wheel alarm, preheating-free alarm, acceleration and deceleration emergency alarm, bucket lifting and reversing alarm, parking brake alarm and the like after processing the state parameters, and comprehensively evaluate the performance, economy and operation level of a truck driver of the truck through the performance indexes.
Drawings
FIG. 1 is a radar chart of truck performance evaluation;
FIG. 2 is a graph of yield;
FIG. 3 is a graph of operational smoothness;
FIG. 4 is a graph of energy consumption for this class;
FIG. 5 is a graph of the driving range of the present class;
FIG. 6 is a graph of average efficiency;
fig. 7 is a safety index graph.
Detailed Description
The invention is further described below with reference to the drawings and examples.
The invention provides a method for evaluating the performance of a strip mine truck, which comprises the following steps:
1. collecting real-time data of truck operation
Real-time data of truck operation is collected, including real-time data of truck GPS longitude KCJD, truck latitude KCWD, electric shovel GPS longitude DCJD, electric shovel latitude DCWD, truck speed KCSD, GPS vehicle speed GPSCS, truck lift bucket KCJD, engine speed FDJZS, parking brake ZCDD and generator net power JGL.
2. Processing real-time data
The real-time data of the secondary processing truck is used for obtaining truck yield CL, average energy consumption PJNH, operation stability CZPWX, average efficiency PJXL, total electric consumption ZHDL, total mileage ZLCS, accumulated acceleration LJJSD, total driving time ZJSJ, truck overspeed alarm, spinning wheel alarm, non-preheating alarm, acceleration and deceleration emergency alarm, lift bucket reversing alarm and parking brake alarm performance indexes, wherein the calculation formulas of the performance indexes are as follows:
1) Truck yield
The truck yield is calculated by using GPS longitude and latitude coordinates of the truck and the electric shovel and truck speed information, and the method comprises the following steps of:
(1) Calculating the distance between the truck and the electric shovel:
(2) Determining a "load" state:
assume a loading radius of 20 meters (adjustable). Timing begins when the distance between the truck and the electric shovel is less than the loading radius and KCSD < 1. When the timer is greater than 40 seconds (adjustable), the truck is determined to be in a 'loading state', and the 'loading state' is set to 1. When the distance between the truck and the electric shovel is larger than the loading radius, the loading state is set to 0, and the timing is also set to 0.
(3) Counting the number of truck yield vehicles:
firstly, a central point of the unloading area is determined by using GPS coordinates, then, the radius of the unloading area is determined by taking the central point as the center, and the unloading area is planned to be a circular area. And replacing the positioning coordinates of the electric shovel with coordinates of a central point of the unloading area by using a formula for calculating the distance between the electric shovel and the truck, and judging that the electric shovel enters the unloading area if the distance between the truck and the central point is smaller than the radius of the unloading area. When "loading state" is set to 1, the associated "yield calculation state" is also set to 1 at the same time, but when "loading state" is set to 0, the "yield calculation state" is not followed by setting to 0. When the "yield calculation status" is equal to 1 and the GPS position of the truck is within the unloading area while kcjd=1 is detected, the "yield calculation status" is set to 0, and the yield number of vehicles is increased by 1. When the "yield calculation status" is equal to 1 and the GPS position of the truck is not within the unloading area while kcjd=1 is detected, the yield calculation status is set to 0, and the abnormal yield number of vehicles is increased by 1.
(4) Truck yield was calculated:
yield = truck yield number x 220T
Wherein 220 is the truck full load.
2) Average energy consumption
The average energy consumption is counted and calculated by taking shifts as the period, the energy consumption is smaller when the value is emptied and recalculated at the end of each shift.
The calculation formula is as follows:
PJNH＝ZHDL÷ZLCS
the ZHDL is realized by accumulating JGL and calculated interval duration;
ZLCS is realized by KCSD and calculating interval duration.
3) Stability of operation
The operational smoothness is the rate of change of the truck speed, the more smooth the rate of change, the better the operational smoothness of the truck driver. The operational stationarity is counted and calculated with shift as a period, and is emptied and recalculated at the end of each shift, the smaller the value is, the more stationary.
The calculation formula is as follows:
CZPWX＝LJJSD÷ZJSSJ。
wherein, LJJSD is realized by continuously accumulating the |KCSD_1-KCSD| in each calculation period, wherein KCSD_1 is KCSD 1 second before the calculation time; ZJSSJ is achieved by continuously accumulating the computation cycle duration at KCSD >0 in each computation cycle.
4) Average efficiency
The average efficiency of the truck is counted and calculated on a shift-by-shift basis, with each shift being emptied and recalculated at the end, the smaller the value the higher the efficiency.
The calculation formula is as follows:
PJXL＝ZJSSJ÷CL
5) Safety index
The safety index of the truck is the sum of the alarm times of equipment such as overspeed alarm, spinning wheel alarm, non-preheating alarm, acceleration and deceleration emergency alarm, bucket lifting and reversing alarm, parking brake alarm and the like, and the lower the value is, the safer the lower the value is.
(1) Overspeed alarm: and alarming when KCSD is more than 32 km/h.
(2) Spinning wheel alarming: the KCSD 8 seconds before the calculation time was taken and counted as kcsd_8, and if kcsd_8>5 and the calculation time gpscs=0, an alarm was given.
(3) And (5) non-preheating alarm: the FDJZS starts timing when it rises from 0 to 700, and alarms if KCSD >0 within 5 minutes.
(4) Acceleration and deceleration emergency alarm: taking the KCSD before the calculation time of 1 second, calculating the KCSD as KCSD_1, and alarming if the calculation time is |KCSD_1-KCSD| > 5.
(5) And (5) bucket lifting reversing alarm: when kcjd=1, alarm if KCSD < -0.5 km/h.
(6) Number of parking brake errors: when zzd=1, alarm if |kcsd| > 0.
3. Establishing a radar chart for evaluating truck performance
As shown in fig. 1, radar chart analysis is performed on truck performance indexes such as truck yield, average energy consumption, operation stability, average efficiency, safety index and the like obtained by secondary processing, so as to obtain a truck performance evaluation system.
The truck data model shows five indexes of truck yield, average energy consumption, operation stability, average efficiency and safety index in the form of a radar map, wherein the higher the yield is, the more the radar map is filled, the smaller the operation stability value is, the more the radar map is filled, the smaller the average energy consumption is, the more the radar map is filled, the smaller the average efficiency is, the more the radar map is filled, and the smaller the safety index is, the more the radar map is filled. The larger the overall fill area of the radar chart, the better the performance of the truck.
4. Evaluation of truck Performance and actual operating level
Real-time scoring is performed according to the truck performance radar chart, and the truck performance and the operation level of a driver are evaluated. The performance indexes are respectively plotted, and the performance of the truck and the operation level of a truck driver can be analyzed through the curves.
As shown in fig. 2 and 3, the present shift yield curve and the present shift operational stability curve are plotted.
The average energy consumption curves respectively draw the curves of the energy consumption of the present shift and the driving mileage of the present shift, as shown in fig. 4 and 5.
Further, an average efficiency curve and a safety index curve are included as shown in fig. 6 and 7.
Claims (1)
1. The method for evaluating the performance of the strip mine truck is characterized by comprising the following steps of:
1) Collecting real-time data of truck operation
Collecting real-time data of truck operation, including real-time data of truck GPS longitude KCJD, truck latitude KCWD, electric shovel GPS longitude DCJD, electric shovel latitude DCWD, truck speed KCSD, GPS speed GPSCS, truck lift bucket KCJD, engine speed FDJZS, parking brake ZCDD and generator net power JGL;
2) Processing real-time data
The real-time data of the secondary processing truck is used for obtaining truck yield CL, average energy consumption PJNH, operation stability CZPWX, average efficiency PJXL, total electric consumption ZHDL, total mileage ZLCS, accumulated acceleration LJJSD, total driving time ZJSJ, truck overspeed alarm, spinning wheel alarm, non-preheating alarm, acceleration and deceleration emergency alarm, lift bucket reversing alarm and parking brake alarm performance indexes;
the calculation formula of the performance index is as follows:
truck yield, calculated as follows:
yield = truck yield number x 220T
Wherein 220 is the truck full load;
average energy consumption, the formula of calculation is:
PJNH＝ZHDL÷ZLCS
the ZHDL is realized by accumulating JGL and calculated interval duration;
ZLCS is realized by KCSD and calculating interval duration in an accumulated way;
operational stability, the formula of calculation is:
CZPWX＝LJJSD÷ZJSSJ
wherein, LJJSD is realized by continuously accumulating the |KCSD_1-KCSD| in each calculation period, wherein KCSD_1 is KCSD 1 second before the calculation time; ZJSJ is realized by continuously accumulating the calculation period duration when KCSD >0 in each calculation period;
average efficiency, the calculation formula is:
PJXL＝ZJSSJ÷CL
the safety index is the sum of the alarm times of truck overspeed alarm, spinning wheel alarm, non-preheating alarm, acceleration and deceleration emergency alarm, bucket lifting and reversing alarm and parking brake alarm equipment, and the lower the value is, the safer the value is;
(1) Overspeed alarm: alarming when KCSD is more than 32 km/h;
(2) Spinning wheel alarming: taking KCSD before the calculation time of 8 seconds, calculating the KCSD as KCSD_8, and alarming if KCSD_8>5 and the calculation time GPSCS=0;
(3) And (5) non-preheating alarm: starting timing when FDJZS rises from 0 to 700, and alarming if KCSD >0 in 5 minutes;
(4) Acceleration and deceleration emergency alarm: taking the KCSD before the calculation time of 1 second, calculating the KCSD as KCSD_1, and alarming if the calculation time is |KCSD_1-KCSD| > 5;
(5) And (5) bucket lifting reversing alarm: when KCJD=1, alarm if KCSD < -0.5 km/h;
(6) Number of parking brake errors: when zzd=1, alarm if |kcsd| > 0;
3) Establishing a radar chart for evaluating truck performance
Carrying out radar chart analysis on truck yield, average energy consumption, operation stability, average efficiency and safety index truck performance indexes obtained by secondary processing to obtain a truck performance evaluation system;
4) Evaluation of truck Performance and truck driver operating level
Real-time scoring is performed according to the truck performance radar chart, and the truck performance and the operation level of a driver are evaluated.
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Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2009126503A (en) * | 2007-11-28 | 2009-06-11 | Sumitomo Electric Ind Ltd | Driving evaluation device, driving evaluation system, computer program and driving evaluation method |
| CN103268539A (en) * | 2013-05-21 | 2013-08-28 | 北京速力科技有限公司 | Open-cast mining GPS truck intelligent dispatching system |
| CN105575115A (en) * | 2015-12-17 | 2016-05-11 | 福建星海通信科技有限公司 | Driving behavior analysis method based on vehicle-mounted monitoring and management platform |
| CN105730450A (en) * | 2016-01-29 | 2016-07-06 | 北京荣之联科技股份有限公司 | Driving behavior analyzing method and evaluation system based on vehicle-mounted data |
| CN105974886A (en) * | 2016-06-28 | 2016-09-28 | 华中科技大学 | Health monitoring method for numerical control machine tool |
| CN106296474A (en) * | 2016-07-22 | 2017-01-04 | 厦门大学 | A kind of loader working condition complexity recognition methods |
| CN106990763A (en) * | 2017-04-20 | 2017-07-28 | 浙江大学 | A kind of Vertical Mill operation regulator control system and method based on data mining |
| CN110033136A (en) * | 2019-04-17 | 2019-07-19 | 扬州亚星客车股份有限公司 | A kind of data analysing method of the electric motor coach based on monitor supervision platform |
| CN110645985A (en) * | 2019-09-26 | 2020-01-03 | 东北大学 | Voice navigation system and method for strip mine truck |
-
2020
- 2020-04-14 CN CN202010291228.6A patent/CN111461568B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2009126503A (en) * | 2007-11-28 | 2009-06-11 | Sumitomo Electric Ind Ltd | Driving evaluation device, driving evaluation system, computer program and driving evaluation method |
| CN103268539A (en) * | 2013-05-21 | 2013-08-28 | 北京速力科技有限公司 | Open-cast mining GPS truck intelligent dispatching system |
| CN105575115A (en) * | 2015-12-17 | 2016-05-11 | 福建星海通信科技有限公司 | Driving behavior analysis method based on vehicle-mounted monitoring and management platform |
| CN105730450A (en) * | 2016-01-29 | 2016-07-06 | 北京荣之联科技股份有限公司 | Driving behavior analyzing method and evaluation system based on vehicle-mounted data |
| CN105974886A (en) * | 2016-06-28 | 2016-09-28 | 华中科技大学 | Health monitoring method for numerical control machine tool |
| CN106296474A (en) * | 2016-07-22 | 2017-01-04 | 厦门大学 | A kind of loader working condition complexity recognition methods |
| CN106990763A (en) * | 2017-04-20 | 2017-07-28 | 浙江大学 | A kind of Vertical Mill operation regulator control system and method based on data mining |
| CN110033136A (en) * | 2019-04-17 | 2019-07-19 | 扬州亚星客车股份有限公司 | A kind of data analysing method of the electric motor coach based on monitor supervision platform |
| CN110645985A (en) * | 2019-09-26 | 2020-01-03 | 东北大学 | Voice navigation system and method for strip mine truck |
Non-Patent Citations (3)
| Title |
|---|
| "Driving Performances Assessment Based on Speed Variation Using Dedicated Route Truck GPS Data";Ying Li 等;《IEEE Access 》;20190409;全文 * |
| 改进雷达图评价方法在汽车综合性能评价中的应用;陈勇等;《吉林大学学报(工学版)》;20111115(第06期);全文 * |
| 露天矿卡车调度系统性能评价指标的研究;陈冲等;《矿冶》;20060930(第03期);全文 * |
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