CN106096593A - A kind of recognition methods of the effective operation section loading mechanical shovel process of assembling - Google Patents
A kind of recognition methods of the effective operation section loading mechanical shovel process of assembling Download PDFInfo
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- CN106096593A CN106096593A CN201610585014.3A CN201610585014A CN106096593A CN 106096593 A CN106096593 A CN 106096593A CN 201610585014 A CN201610585014 A CN 201610585014A CN 106096593 A CN106096593 A CN 106096593A
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- 238000000034 method Methods 0.000 title claims abstract description 31
- 230000008569 process Effects 0.000 title abstract description 11
- 238000000605 extraction Methods 0.000 claims abstract description 11
- 239000000284 extract Substances 0.000 claims abstract description 6
- 230000000694 effects Effects 0.000 claims abstract description 5
- 230000008859 change Effects 0.000 claims description 23
- 238000001914 filtration Methods 0.000 claims description 19
- 239000000463 material Substances 0.000 claims description 17
- 238000009795 derivation Methods 0.000 claims description 7
- 230000011218 segmentation Effects 0.000 claims description 5
- 230000009471 action Effects 0.000 claims description 3
- 238000004458 analytical method Methods 0.000 abstract description 10
- 238000001228 spectrum Methods 0.000 abstract description 8
- 238000007405 data analysis Methods 0.000 abstract description 2
- 238000007619 statistical method Methods 0.000 abstract description 2
- 238000007599 discharging Methods 0.000 description 5
- 238000010586 diagram Methods 0.000 description 3
- 230000007812 deficiency Effects 0.000 description 2
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 2
- 230000001154 acute effect Effects 0.000 description 1
- 230000004888 barrier function Effects 0.000 description 1
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- 238000005516 engineering process Methods 0.000 description 1
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- 238000012986 modification Methods 0.000 description 1
- 230000035772 mutation Effects 0.000 description 1
- 238000000926 separation method Methods 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
- G06F2218/02—Preprocessing
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
- G06F2218/08—Feature extraction
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- Operation Control Of Excavators (AREA)
Abstract
The present invention relates to a kind of loader effective operation section recognition methods, step is as follows: 1) obtains rotating bucket big cavity pressure signal, swing arm big cavity pressure signal from loader, extracts rotating bucket big cavity pressure signal, the duty cycle of swing arm big cavity pressure signal；2) according to the duty cycle obtained, to the job step in duty cycle according to the characteristic information of predefined effective operation section, job step extraction is carried out, it is achieved the identification of effective operation section.The present invention defines effective operation section, the division of loader sessions, is advantageously implemented the analysis to operation process, the particularly analysis to working condition identification.And the effective operation section identification of operation spectrum is realized according to the characteristic information of effective operation section；The be identified as analysis of working condition, the data analysis of operation spectrum and the volume spectrum etc. of effective operation section play the effect laid the foundation；It is advantageously implemented the refinement to operation modal data, it is simple to carry out statistical analysis, makes operation modal data more Regularization.
Description
Technical field
The present invention relates to the recognition methods of engineering truck effective operation section, load mechanical shovel dress more particularly, it relates to a kind of
The recognition methods of the effective operation section of process.
Background technology
Along with the large-scale national project such as China's mining, building, water conservancy and hydropower, High-speed Railway Network, network of highways, the south water to north is built
If quickly propel, the product of engineering truck, sales volume and recoverable amount quickly improve, and engineering machinery undergoes an unusual development rapidly.Engineering machinery
The product of more than 95% uses hydraulic power, in order to obtain high pulling torque, large inertia load requirements, owing to working environment is severe, makees
Industry operating mode is complicated and changeable, and the improving constantly of equipment automatization, the level of informatization, and how to guarantee that engineering machinery is reliable, efficiently
Operation, be technical barrier the most urgently to be resolved hurrily.In order to solve these difficult problems, it is necessary to the operation of loader is composed and carries out point
Analysis, including extraction, sessions analysis and the identification etc. of working condition of duty cycle.
Wherein, the effect taken over from the past and set a new course for the future is played in sessions analysis in operation analysis of spectrum, the most effectively carries out segmentation,
Vital relation is played in working condition identification etc. later.
The operating type of loader has " V " type operation, " I " type operation, " L " type operation, T-shape operation etc., according to original
Job step criteria for classification mainly comprise 6 job steps, i.e. unloaded advances, spading, fully loaded retreat, be fully loaded with advance, discharging, zero load
Retreat, as shown in Figure 1.As loader is previous at initial spading about 10 meters from stockpile, thus start before stockpile zero load
Entering, the teamwork such as swing arm and rotating bucket after material, start spading material, material scraper is return original place after reversing gear after completely struggling against, is connect
To be fully loaded with after turning to and drive towards dumper, the teamwork again of swing arm and rotating bucket, lift bucket discharging after dumper, after completing discharging
Exit original place, shovel process of assembling the most next time.
Owing to original job segmentation criteria is to divide according to operation process, classification number is many, causes identification difficulty big, part
Segment information repeats and inessential.
Summary of the invention
It is an object of the invention to overcome the deficiencies in the prior art, it is provided that a kind of definition effective operation section, and according to effectively
The characteristic information of job step realizes the loader effective operation section recognition methods of operation spectrum.
Technical scheme is as follows:
A kind of loader effective operation section recognition methods, effective operation section includes spading, heavy haul transport, discharging, and step is such as
Under:
1) from loader, obtain rotating bucket big cavity pressure signal, swing arm big cavity pressure signal, extract rotating bucket big cavity pressure letter
Number, the duty cycle of swing arm big cavity pressure signal；
2) according to the duty cycle that obtains, to the job step in duty cycle according to the feature of predefined effective operation section
Information, carries out job step extraction, it is achieved the identification of effective operation section.
As preferably, step 2) described in the characteristic information of effective operation section be default specific threshold, by specific
Threshold value extracts the waypoint of each job step.
As preferably, effective operation section omits the unloaded advance of standard operation section, unloaded retrogressing, and heavy haul transport includes standard
The fully loaded retrogressing of acting section, fully loaded advance.
As preferably, the minimum point before swing arm big cavity pressure contacting material is defined as spading job step start time point；
First maximum point of the big cavity pressure of rotating bucket is defined as spading job step end time point；
Heavy haul transport job step initial time is spading job step end time point；Before unloading materials, the big cavity pressure of rotating bucket
It is heavy haul transport job step end time point more than the time point of the change threshold values preset；
Discharge operation section initial time is heavy haul transport job step end time point；After unloading materials, the big cavity pressure of swing arm
The minimum point reached is defined as discharge operation section end time point；
Then effective operation section includes tetra-waypoints of A1, A2, A3 and A4.
As preferably, the extraction of the waypoint of each job step particularly as follows:
2.1) cavity pressure big to swing arm carries out minimum point and asks for, and asks for the minimum point B of minimum；Then ask for the most adjacent
The minimum point of nearly minimum minimum point about B, then the minimum point on the left side is waypoint A1, and the minimum point on the right is for dividing
Section point A4；
2.2) then cavity pressure big to rotating bucket carries out first derivation, asks for its rate of change, then cavity pressure big to rotating bucket is asked for
Maximum maximum point C；Then first, the left and right first derivative of closest maximum maximum point C is asked for more than presetting very big threshold values
Change point, then the change point on the left side is waypoint A2, and the change point on the right is waypoint A3.
As preferably, step 2.1) in, first cavity pressure big to swing arm carries out twice iterative filtering, then to twice iterative filtering
After the signal that obtains carry out minimum point and ask for.
As preferably, step 2.2) in, cavity pressure big to rotating bucket carries out twice iterative filtering and 100 iteration filters respectively
Ripple, the numerical value obtaining twice iterative filtering carries out first derivation, asks for its rate of change；To obtain after 100 iterative filterings
Data ask for maximum maximum point C.
Beneficial effects of the present invention is as follows:
Method of the present invention solves the problem that engineer machinery operation section identification is difficult, defines effective operation section, loader
The division of sessions, is advantageously implemented the analysis to operation process, the particularly analysis to working condition identification.And according to having
The characteristic information of effect job step realizes the effective operation section identification of operation spectrum；Effective operation section be identified as working condition point
Analysis, the data analysis of operation spectrum and volume spectrum etc. play the effect laid the foundation.Method of the present invention is advantageously implemented work
The refinement of industry modal data, it is simple to carry out statistical analysis, makes operation modal data more Regularization.
Accompanying drawing explanation
Fig. 1 is in prior art, the standard operation section schematic diagram of loader；
Fig. 2 is in the present invention, the effective operation section schematic diagram of loader；
Fig. 3 is the identification basic framework schematic diagram of the present invention；
Fig. 4 is the flow chart of the effective operation section recognizer of the present invention.
Detailed description of the invention
Below in conjunction with drawings and Examples, the present invention is described in further detail.
The present invention is to solve the impalpable deficiency of effective operation section present in prior art, it is provided that a kind of loader
Effective operation section recognition methods, according to the meaning of effective operation section and to combine the big cavity pressure of swing arm that actual acquisition arrives big with rotating bucket
The characteristic of cavity pressure etc. defines the time range of effective operation section.
Effective operation section refer in operation process with working condition, the closely-related operation process of working environment.In order to more
Good realizes segmentation, and in conjunction with the demand of working condition identification, the present invention proposes the segmentation method of a kind of effective operation section, and carries out
Identification by stages.In the present invention, effective operation section includes spading, heavy haul transport, discharging, as in figure 2 it is shown, effective operation section omits mark
The screwing on advance, unloaded retreat of quasi-job step, heavy haul transport includes the fully loaded retrogressing of canonical action section, fully loaded advances.Effectively make
Industry section mainly considers from the value angle of job step.Owing to, in standard operation section, unloaded advance, unloaded retrogressing etc. are for operating mode
Identify, intelligent gearshift and vehicle performance test-purpose is little, break-up value is little and identifies that difficulty is big, therefore, the present invention is effectively
Job step is not considered；Heavy haul transport section then can be merged into for similar job steps such as fully loaded retrogressing, fully loaded advances
Account for.
Recognition methods of the present invention, key step is as follows:
1) from loader obtain rotating bucket big cavity pressure signal, swing arm big cavity pressure signal, by big for rotating bucket cavity pressure signal,
Swing arm big cavity pressure signal extraction duty cycle；Wherein, it is primarily referred to as each operation of loader spading process duty cycle
The division of circulation section.
2) according to the duty cycle that obtains, to the job step in duty cycle according to the feature of predefined effective operation section
Information, carries out job step extraction, it is achieved the identification of effective operation section.In the present embodiment, the feature letter of described effective operation section
Breath is the specific threshold preset, and is extracted the waypoint of each job step by specific threshold.
In the present invention, the waypoint of each job step is as follows:
Minimum point before swing arm big cavity pressure contacting material is defined as spading job step start time point；The big chamber of rotating bucket is pressed
First maximum point of power is defined as spading job step end time point；
Heavy haul transport job step initial time is spading job step end time point；Before unloading materials, the big cavity pressure of rotating bucket
It is heavy haul transport job step end time point more than the time point of the change threshold values preset；
Discharge operation section initial time is heavy haul transport job step end time point；After unloading materials, the big cavity pressure of swing arm
The minimum point reached is defined as discharge operation section end time point；
Then effective operation section includes tetra-waypoints of A1, A2, A3 and A4.
Specifically, in the present embodiment, spading job step initial time is scraper bowl when contacting with material, and the big cavity pressure of swing arm is opened
Beginning acutely to become big, the big cavity pressure of swing arm has to minimum extreme point before change, and this is owing to before spading, scraper bowl is placed and ground
Face is caused, and now swing arm big cavity pressure value is less than during normal traveling, therefore before definition swing arm big cavity pressure acute variation
Minimum point is spading job step start time point；
The spading job step end time be scraper bowl fill material depart from work surface time, now be typically accompanied by receive bucket action (
As 1-2 time), all can there is a maximum when receiving bucket every time in the big cavity pressure of rotating bucket, and after completing to receive bucket, the big cavity pressure of rotating bucket will
Steadily declining, first maximum point of the definition big cavity pressure of rotating bucket is the spading job step end time.
Heavy haul transport job step initial time is the spading job step end time；
The heavy haul transport job step end time be scraper bowl lifting prepare unloading materials time, now rotating bucket will produce tipping bucket move
Making, the big cavity pressure of rotating bucket occurs to change rapidly, and the change point rapidly of the definition big cavity pressure of rotating bucket is that heavy haul transport job step terminates
Time.
Discharge operation section initial time is the heavy haul transport job step end time；
The discharge operation section end time is scraper bowl when laying down all materials, and swing arm big cavity pressure value can be undergone mutation, and reaches
One minimum point, the minimum point that the definition big cavity pressure of swing arm reaches is the discharge operation section end time.
According to the definition of above-mentioned effective operation section, the Origin And Destination of spading job step is defined as A1, A2, and uses A1A2
Represent spading job step；In like manner, A2A3 represents heavy haul transport job step, and A3A4 represents discharge operation section.
After the periodicity extraction that fulfils assignment, cavity pressure big to the swing arm in each duty cycle and the big cavity pressure of rotating bucket enter respectively
Row analyzing and processing, then the waypoint of each job step extraction particularly as follows:
2.1) cavity pressure big to swing arm carries out minimum point and asks for, and asks for the minimum point B of minimum；Then ask for the most adjacent
The minimum point of nearly minimum minimum point about B, then the minimum point on the left side is waypoint A1, and the minimum point on the right is for dividing
Section point A4；
2.2) then cavity pressure big to rotating bucket carries out first derivation, asks for its rate of change, then cavity pressure big to rotating bucket is asked for
Maximum maximum point C；Then first, the left and right first derivative of closest maximum maximum point C is asked for more than presetting very big threshold values
Change point, then the change point on the left side is waypoint A2, and the change point on the right is waypoint A3.
In order to the result making extraction is more accurate, in the present embodiment, job step extracts main employing iterative filtering and extreme point
The method asked for, extracts the waypoint of each job step by setting specific threshold, as shown in Figure 4, specific as follows:
Step 2.1) in, first cavity pressure big to swing arm carries out twice iterative filtering, and this process mainly makes signal more flat
Sliding, eliminate short-tempered point.Again the signal obtained after twice iterative filtering is carried out minimum point to ask for, ask for the minimum point of minimum
B；Then ask for the minimum point of minimum point about the B of closest minimum, then the minimum point on the left side is waypoint A1, the right
Minimum point be waypoint A4.
Step 2.2) in, cavity pressure big to rotating bucket carries out twice iterative filtering and 100 iterative filterings respectively, to twice
The numerical value that iterative filtering obtains carries out first derivation, asks for its rate of change；The data obtained after 100 iterative filterings are asked for
Maximum maximum point C, carries out 100 iterative filterings, it is possible to eliminate the short-tempered point of the maximum maximum point C of all interference as far as possible.?
After completing first derivation and asking for maximum maximum point C, carry out asking for first, the left and right single order of closest maximum maximum point C
The derivative change point more than 0.5, two points of gained are effective operation section waypoint A2, A3.
So far, whole effective operation section waypoint A1, A2, A3 and A4 is obtained, according to these waypoints to duty cycle
Interior data carry out extracting separation, i.e. can get effective operation section.
Above-described embodiment is intended merely to the present invention is described, and is not used as limitation of the invention.As long as according to this
Bright technical spirit, be changed above-described embodiment, modification etc. all will fall in the range of the claim of the present invention.
Claims (7)
1. a loader effective operation section recognition methods, it is characterised in that effective operation section includes spading, heavy haul transport, unloads
Material, step is as follows:
1) from loader, obtain rotating bucket big cavity pressure signal, swing arm big cavity pressure signal, extract rotating bucket big cavity pressure signal, move
The duty cycle of arm big cavity pressure signal；
2) according to the duty cycle obtained, the job step in duty cycle is believed according to the feature of predefined effective operation section
Breath, carries out job step extraction, it is achieved the identification of effective operation section.
Loader effective operation section recognition methods the most according to claim 1, it is characterised in that step 2) described in have
The characteristic information of effect job step is default specific threshold, is extracted the waypoint of each job step by specific threshold.
Loader effective operation section recognition methods the most according to claim 1, it is characterised in that effective operation section omits mark
The unloaded advance of quasi-job step, unloaded retrogressing, heavy haul transport includes the fully loaded retrogressing of canonical action section, is fully loaded with and advances.
Loader effective operation section recognition methods the most according to claim 2, it is characterised in that the big cavity pressure of swing arm contacts
Minimum point before material is defined as spading job step start time point；First maximum point of the big cavity pressure of rotating bucket is defined as
Spading job step end time point；
Heavy haul transport job step initial time is spading job step end time point；Before unloading materials, the big cavity pressure of rotating bucket is more than
The time point of the change threshold values preset is heavy haul transport job step end time point；
Discharge operation section initial time is heavy haul transport job step end time point；After unloading materials, the big cavity pressure of swing arm reaches
Minimum point be defined as discharge operation section end time point；
Then effective operation section includes tetra-waypoints of A1, A2, A3 and A4.
Loader effective operation section recognition methods the most according to claim 4, it is characterised in that the segmentation of each job step
Point extraction particularly as follows:
2.1) cavity pressure big to swing arm carries out minimum point and asks for, and asks for the minimum point B of minimum；Then ask for closest
The minimum point of little minimum point about B, then the minimum point on the left side is waypoint A1, and the minimum point on the right is waypoint
A4；
2.2) then cavity pressure big to rotating bucket carries out first derivation, asks for its rate of change, then cavity pressure big to rotating bucket asks for maximum
Maximum point C；Then first, the left and right first derivative of closest maximum maximum point C is asked for more than the change presetting very big threshold values
Change point, then the change point on the left side is waypoint A2, and the change point on the right is waypoint A3.
Loader effective operation section recognition methods the most according to claim 5, it is characterised in that step 2.1) in, the most right
The big cavity pressure of swing arm carries out twice iterative filtering, then the signal obtained after twice iterative filtering is carried out minimum point asks for.
Loader effective operation section recognition methods the most according to claim 5, it is characterised in that step 2.2) in, to turning
The big cavity pressure that struggles against carries out twice iterative filtering and 100 iterative filterings respectively, and the numerical value obtaining twice iterative filtering carries out one
Rank derivation, asks for its rate of change；The data obtained after 100 iterative filterings are asked for maximum maximum point C.
Priority Applications (4)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610585014.3A CN106096593B (en) | 2016-07-22 | 2016-07-22 | A kind of recognition methods for the effective operation section loading mechanical shovel dress process |
| US16/067,740 US10633823B2 (en) | 2016-07-22 | 2017-07-03 | Method of identifying a difficulty level of an operating condition of a loader |
| PCT/CN2017/091433 WO2018014718A1 (en) | 2016-07-22 | 2017-07-03 | Method for recognizing difficulty level of working condition of loading machine |
| PCT/CN2017/091399 WO2018014714A1 (en) | 2016-07-22 | 2017-07-03 | Method for recognizing effective operation section in shovelling and loading process of loading machine |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610585014.3A CN106096593B (en) | 2016-07-22 | 2016-07-22 | A kind of recognition methods for the effective operation section loading mechanical shovel dress process |
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| Publication Number | Publication Date |
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| CN106096593A true CN106096593A (en) | 2016-11-09 |
| CN106096593B CN106096593B (en) | 2019-06-04 |
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| CN201610585014.3A Active CN106096593B (en) | 2016-07-22 | 2016-07-22 | A kind of recognition methods for the effective operation section loading mechanical shovel dress process |
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| WO (1) | WO2018014714A1 (en) |
Cited By (5)
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| WO2018014714A1 (en) * | 2016-07-22 | 2018-01-25 | 厦门大学 | Method for recognizing effective operation section in shovelling and loading process of loading machine |
| WO2018014718A1 (en) * | 2016-07-22 | 2018-01-25 | 厦门大学 | Method for recognizing difficulty level of working condition of loading machine |
| CN108978769A (en) * | 2018-07-03 | 2018-12-11 | 柳州柳工挖掘机有限公司 | Excavator operating mode's switch clocking method and system and excavator |
| CN109359524A (en) * | 2018-09-07 | 2019-02-19 | 长安大学 | A kind of loading machine operating mode's switch model construction and recognition methods |
| CN110965597A (en) * | 2019-12-17 | 2020-04-07 | 广西柳工机械股份有限公司 | Automatic shovel loading triggering method, automatic shovel loading triggering device and loader |
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| CN111538953B (en) * | 2020-04-17 | 2023-06-16 | 上海华兴数字科技有限公司 | Material identification method, device, equipment and storage medium |
| CN113882457B (en) * | 2021-09-27 | 2023-02-14 | 徐州徐工挖掘机械有限公司 | Hydraulic excavator working condition identification and statistics method and system and hydraulic excavator |
| CN115264047B (en) * | 2022-07-18 | 2023-05-02 | 华侨大学 | Automatic gear shifting method, device and equipment of electric loader and storage medium |
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Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2018014714A1 (en) * | 2016-07-22 | 2018-01-25 | 厦门大学 | Method for recognizing effective operation section in shovelling and loading process of loading machine |
| WO2018014718A1 (en) * | 2016-07-22 | 2018-01-25 | 厦门大学 | Method for recognizing difficulty level of working condition of loading machine |
| US10633823B2 (en) | 2016-07-22 | 2020-04-28 | Xiamen University | Method of identifying a difficulty level of an operating condition of a loader |
| CN108978769A (en) * | 2018-07-03 | 2018-12-11 | 柳州柳工挖掘机有限公司 | Excavator operating mode's switch clocking method and system and excavator |
| CN108978769B (en) * | 2018-07-03 | 2021-03-16 | 柳州柳工挖掘机有限公司 | Excavator working condition identification timing method and system and excavator |
| CN109359524A (en) * | 2018-09-07 | 2019-02-19 | 长安大学 | A kind of loading machine operating mode's switch model construction and recognition methods |
| CN109359524B (en) * | 2018-09-07 | 2021-06-22 | 长安大学 | Loader condition identification model construction and identification method |
| CN110965597A (en) * | 2019-12-17 | 2020-04-07 | 广西柳工机械股份有限公司 | Automatic shovel loading triggering method, automatic shovel loading triggering device and loader |
| CN110965597B (en) * | 2019-12-17 | 2022-02-15 | 广西柳工机械股份有限公司 | Automatic shovel loading triggering method, automatic shovel loading triggering device and loader |
Also Published As
| Publication number | Publication date |
|---|---|
| WO2018014714A1 (en) | 2018-01-25 |
| CN106096593B (en) | 2019-06-04 |
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