CN102556783A - Subarea-based elevator traffic prediction group control method and elevator monitoring implementation - Google Patents
Subarea-based elevator traffic prediction group control method and elevator monitoring implementation Download PDFInfo
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- CN102556783A CN102556783A CN2011101931878A CN201110193187A CN102556783A CN 102556783 A CN102556783 A CN 102556783A CN 2011101931878 A CN2011101931878 A CN 2011101931878A CN 201110193187 A CN201110193187 A CN 201110193187A CN 102556783 A CN102556783 A CN 102556783A
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
- Y02B50/00—Energy efficient technologies in elevators, escalators and moving walkways, e.g. energy saving or recuperation technologies
Abstract
The invention discloses a subarea-based elevator traffic prediction group control method and elevator monitoring implementation, which include allocation of the elevators in floor subareas, a subarea-based group control traffic mode recognition method and elevator monitoring implementation, wherein rational allocation of the elevators in the subareas solves the problem of inconvenience of inter-area traffic and eases the problem of congestion of the elevators in the subareas during morning-evening rush hours; the subarea-based group control traffic mode recognition method recognizes the traffic flow through a fuzzy neural network, so that the problem that operating states of the elevators in the subareas are different in traffic idleness and occupancy is solved; and a multi-area monitoring system and an individual inter-area monitoring system are employed to simplify the problem of monitoring of the complicated building floor elevators. The subarea-based elevator traffic prediction group control method and the elevator monitoring implementation can be widely used for optimizing the multipurpose elevators in high-rise or super high-rise residential or office buildings, energy-saving capacity is achieved, and satisfaction degree and efficiency for riding the elevators are improved.
Description
Technical field
The present invention a kind ofly is applied to dwelling house or the multiduty floor elevator prioritization scheme of handling official business, and it comprises based on the team control transit mode recognition methods of the allocation of elevators of floor subregion, subregion and elevator monitoring system.
Background technology
Along with the propelling of urbanization process with technology, the urban skyscraper is intellectuality and functional diversities more and more, owing to elevator is also played an important role in skyscraper, so also presented diversified trend at the elevator group controlling field of research.At present; Elevator vertical transportation area research is placed on travel forecasting and the dispatching algorithm to the skyscraper of special purpose mostly; This is based on ideal and uniform skyscraper, and in real life, the skyscraper that function is complicated can be found everywhere; Especially be embodied in the skyscraper of commercial office usefulness, actual demand just may not be well satisfied in so above research.
Generally speaking, for the high level or the high-rise building of functional diversities demand, need subregion to carry out the control of elevator; When architectural scale bigger; The number of plies is more than 30 layers the time, and the vertical traffic in the building should be divided into several districts, and each district is served by the elevator of different capabilities and speed.Having a look static and dynamic subregion earlier divides:
So-called static partition is exactly that one group of elevator of fixed allocation goes to serve adjacent several regions, and the problem of existence is that the fixed partition meeting causes elevator busy not busy uneven, the traffic characteristics that becomes when being difficult to adapt to; The partitioned area of dynamic partition then depends on the distribution of passenger flow; According to the difference of flow of traffic and dynamically adjust the zone of subregion; The problem that exists is number of regions and each regional scope, depends on the transition condition of each car, position and direction; Thereby algorithm is very complicated, also can cause the unreasonable of scheduling simultaneously.
Though subregion has above characteristics and deficiency, yet in real life, the static partition of skyscraper elevator is in the great majority, and is mostly simple static partition, because it has such advantage:
1. reasonably static partition can reduce number of stops, shortens the time that elevator comes and goes a week.We know that the number of times of elevator parking is many more, and energy consumption is big more, so will reduce start-stop time as far as possible.On the other hand, the energy consumption of the energy consumption during the elevator full speed running during well below acceleration, deceleration so the subregion arrangement can effectively reduce the start-stop time of elevator, thereby reaches the bulk life time that prolongs elevator group and the purpose of energy savings.
2. reasonably static partition can reduce the expense (like the loss that elevator stops and brings, Room door expense) of lift facility simultaneously, and saves building area (number as saving elevator Hou Tingmen is beneficial to other use).
In sum, if can realize travel forecasting or the Based Intelligent Control of scheduling and monitoring, thereby the deficiency of the traffic characteristics that becomes when remedying its subregion and being difficult to adapt to then has very important practical sense to the static partition of elevator.
Summary of the invention
The object of the invention mainly is to following problem: the 1. inconvenient problem of the trans-regional traffic that occurs of subregion elevator; 2. the prediction of passenger's magnitude of traffic flow is not considered in the control of subregion elevator, thereby causes the busy not busy uneven problem of some elevator operation; 3. the complicated disadvantageous problem of bringing to monitoring of skyscraper function.Below above problem, carried out certain exploration and improvement, its summary of the invention comprises:
1. be the inconvenient problem that solves the trans-regional traffic of subregion elevator appearance; The present invention is optimized configuration to the dwelling house or the multiduty floor subregion elevator of handling official business; Set up transregional interlayer Hou Tingqu, its characteristics are that its arrangement generally is located at the maximum layer floor of one's respective area with lower area, are convenient to like this get into another zone from a zone; Simultaneously, the elevator of trans-regional interfloor traffic is furnished with special trans-regional cluster control unit and controls separately.Generally be in fast mode when transregional when launching first function, thereby improved the rapidity of trans-regional communications and transportation, reach the purpose that reduces passenger journey time with ladder.Need should be mentioned that when transregional when launching second function that at this it also will be undertaken and be used for alleviating the task of commuter rush hour pressure sooner or later with ladder.
2. for the not busy busy uneven problem of the elevator traffic that fixedly division brought that solves the subregion elevator, the present invention adopts fuzzy neural network algorithm that their transit mode is discerned.In this process; To be interlayer transit mode and trans-regional interfloor traffic pattern in the zone to the interfloor traffic mode division, the transit mode below having formed like this: interlayer transit mode, trans-regional interfloor traffic pattern and idle transit mode in up peak mode, lowering peak pattern, the zone.
3. for solving the complicated disadvantageous problem of bringing to monitoring of skyscraper function, the present invention adopts multi partition monitoring system and independent transregional monitoring system, realizes the simplification monitoring of complicated skyscraper, has improved timeliness of monitoring.Main contents are based on cluster control unit in the Embedded zone and trans-regional cluster control unit; They can be connected with the pstn telephone net with the CAN bus communication module; Be responsible for carrying out the dynamic assignment of real-time elevator group controlling network outgoing call sequence, can the information state of each single ladder be sent to long distance control system simultaneously with the mode of multithreading.
Description of drawings
Fig. 1 is that the dwelling house or the multiduty floor subregion elevator of handling official business are distributed system construction drawing rationally;
Fig. 2 is the structure of fuzzy neural network figure that is used for the elevator traffic pattern-recognition;
Fig. 3 is the monitoring scheme drawing of elevator group controlling device in the zone;
Fig. 4 is the monitoring scheme drawing of trans-regional elevator group controlling device;
Fig. 5 is the remote monitor and control diagram of circuit.
The specific embodiment
Have a talk about the specific embodiment of the present invention below in conjunction with accompanying drawing.
The dwelling house shown in Figure 1 or the multiduty floor subregion elevator of handling official business are distributed system construction drawing rationally.Floor is divided into three zones, is respectively low layer region, middle layer region, high-rise zone; Simultaneously, be provided with transregional interlayer marquis ladder in interregional linking section, its optimization characteristics are following:
1) each zone all is respectively equipped with specially ladder and transregional with ladder of interlayer, and specially ladder of interlayer is launched in each zone, launches corresponding low speed and express elevator according to high different height in low, and the special lift in each zone only uses between the internal layer of one's respective area.For example, have the passenger to arrive high-rise zone from bottom, the express elevator of being taken will be respectively through low layer region and middle layer region, does not throughly give middle stop to high-rise zone.
2) mention in the above with ladder for transregional; It has two functions: when transregional when being in first function with ladder; Promptly be used for transregional interfloor traffic; It generally occurs in removes in one day sooner or later some time periods on peak up and down, generally launches fast mode, thereby has improved the rapidity of trans-regional communications and transportation.For example, passenger's layer region from low layer region arrives is arranged, just can take the transregional top layer of using ladder to launch the low layer region of fast mode arrival and get into transregional interlayer Hou Tingqu, the transregional ladder entering destination of using of layer region in taking then; Transregional another function with ladder is to be used for two other time period; Promptly undertaking and alleviating the task of commuter rush hour sooner or later; It is to be noted owing to transregional use with ladder is free section; Specified time is launched specific transit mode, so account for terraced situation for the transregional confusion that for ladder, generally can not take place.
What Fig. 2 provided is the constructional drawing of fuzzy neural network.Comprise input layer, obfuscation layer, rules layer, synthetic layer and output layer respectively.We know that fuzzy neural network can organically combine neural network and fuzzy logic, and neural network can be through obtaining knowledge and improving self performance to environment learning, and its learning process is exactly to revise the process of coefficient of weight, finally can reach expectation value.The shortcoming of neural network itself is that its internal information implies, and neural network is a kind of black box formula structure, and the global optimization approximation capability is restricted.And fuzzy technology is logical reasoning ability, can handle accurate information and fuzzy message, can realize particularity association and mapping.The coefficient of weight that not enough is in the subordinate function is fixed, and can not change according to different passenger flow patterns, can't carry out self study.If these two kinds of methods are combined, adopt nerual network technique to carry out fuzzy message and handle, and then overcome that neural network structure is difficult to confirm and fuzzy logic does not have the shortcoming of self-learning function, can effectively bring into play its advantage separately.
Concrete fuzzy neural network is following for the identification step of the magnitude of traffic flow:
1. confirm the eigenwert of transit mode identification;
2. confirm the structure of fuzzy neural network.
At first, confirm the eigenwert of transit mode identification.Obtaining of flow of traffic can be through following approach:
1) weighting apparatus.As a rule LOAD CELLS is equipped with in elevator bottom, detecting the load state of car, with this weighting apparatus can be rough acquisition passenger flow volume information, suppose a passenger's average weight, just can obtain at a certain floor entering elevator and leave the number of elevator.
2) infrared detecting device.In the elevator door both sides and top and bottom infrared emission and detecting device are housed, pass in and out situation and obtain passenger flow volume information thereby can detect the passenger comparatively accurately.
3) purpose floor call equipment.This equipment makes the passenger directly select the purpose floor at balcony, through to exhaling the record of ladder, can follow the tracks of the intensity and the flow direction of passenger flow exactly.
4) computer vision apparatus.Through the application image recognition technology, can accurately obtain passenger flow information.
Total passenger traffic in accordance with the time period
entrance hall traffic
go lobby traffic
and inter regional traffic
inter-regional level
Traffic
five characteristic values for fuzzy neural network identification.Because the subregion cluster control unit only is responsible for the specially control of ladder of interlayer; And transregional crowd
only is responsible for transregional control with ladder; When discerning the magnitude of traffic flow, we also will be divided into two parts, promptly to the identification of each subregion transit mode and the identification of
territory interfloor traffic pattern.
Each subregional transit mode can be divided into 12 kinds of patterns:
That is: go up the peak pattern by force, descend the peak pattern by force, strong regional internal layer inter mode; Strong mixed mode, last peak pattern, following peak pattern; District's
interlayer pattern, mixed mode, the weak peak pattern that goes up; Weak peak pattern down, weak regional internal layer inter mode, weak mixed mode.
Trans-regional interfloor traffic pattern can be divided into 3 kinds.
That is: strong trans-regional interlayer pattern, trans-regional layer is asked pattern, a little less than trans-regional interlayer pattern.
Secondly; Characteristic according to various transit modes; Can formulate fuzzy rule; To confirm the structure of fuzzy neural network, be identified as example with each subregional friendship
formula, step is following:
1. the input of input layer is:
X wherein
MaxIt is unit
The maxim of the total passenger flow volume of section;
2. obfuscation layer: each fuzzy subset's meaning of total passenger flow volume of this time period
is respectively ' by force ', ' in ', ' weak ' three nodes; Other
each fuzzy subset's meaning is: ' greatly ', ' in ', ' little ', so the node number is 12;
3. rules layer and synthetic layer: the training of the 3rd layer of rules layer and the 4th layer of synthetic layer adopted according to expertise formulate fuzzy rule, rule
expression-form is the if-and-then form ".For example: the if rate of traffic flow is that the up passenger flow proportion of strong and is that the descending passenger flow proportion of big and is that interlayer passenger flow proportion is that little Then transit mode is strong up peak mode in the zonule; Synthetic layer is then with representing with high and low two fuzzy subsets;
4. output layer: the number of output is 4, preceding two that represent traffic intensity, and latter two can represent that its different combinations can organize peak pattern up and down with 0 and 1, mixed mode, and regional internal layer inter mode so just can be combined into 12 kinds of transit modes.Thus; Each subregion
transit mode is divided then confirming as of structure of fuzzy neural network: the input number is 4; The output number is 4; Input fuzzy subset number 3, the number that subclass is stuck with paste in output is 2, each node layer number is respectively 4-12-27-8-4.Will carry out the structure employing BP network that back training nerve net
neural network is handled in normalization method for this neural network, learning function adopts the gradient descending training function traingdx of momentum and self adaptation 1rBP.
Yet; To trans-regional interfloor traffic mode division because its traffic identification is simple; Delimit a model
according to the situation of trans-regional interlayer passenger flow volume
and confirm that transit mode is strong trans-regional interlayer pattern, trans-regional interlayer pattern or a little less than trans-regional interlayer pattern get final product.
Fig. 3 has provided the monitoring scheme drawing of regional interior elevator group controlling device; The object of its monitoring is the special lift in each subregion, and general the platform interlayer is specially terraced at the most according to one of
flow arrangement.At first; The monitoring of elevator performance situation is responsible for by each electric life controller, the signal
that needs to detect down some:
1. elevator door open and close condition monitoring;
2. elevator speed monitoring;
3. motor status monitoring (heating, the phase failure, anti-phase, phase sequence problem);
4. car leveling accuracy position monitoring;
The spacing detection signal in elevator operation end station (for prevent elevator rush to summit with pier at the bottom of);
6. car load capacity monitoring.
Secondly, the control monitor unit of elevator group controlling device comprises in the zone: external equipment, flush bonding processor, SOCKET MODEM module bonded assembly long-range
district, CAN bus communication module and single terraced controller.Each several part is monitored as follows:
1. external equipment comprises the EFPROM circuit that external trouble diagnosing is used; Program store FLASH, modules such as data memory SDRAM and relevant
position, clock, fault pre-alarming read-out.The eeprom memory that wherein extends out is used for the parameter of trouble diagnosing elevator; Failure symptom
is because of waiting database information; Program store FLASH application storing code and parameter etc., data memory SDRAM is used to deposit fully single
system device ephemeral data and program.
2. the cluster control unit in the zone adopts flush bonding processor, can adopt MPC850 series, and it is connected to each single terraced controller with the CAN bus communication, receives each single scalariform attitude information and exhales terraced information, and send control command and give each single ladder; Cluster control unit and SOCKET MODEN module are connected to the pstn telephone network interface in the zone, can each elevator running condition of CAN communication acquisition delivered to remote monitoring center and on Internet, monitor on the net.
3.CAN bus is used for the reliability and stability that multiple lift control system can improve system communication performance and system greatly, it is responsible for delivering to cluster control unit to the running condition and the information of each single terraced controller, and the control command of cluster control unit is passed to each single terraced controller.If break down problem in each elevator; We can discern the running state of elevator according to the failure message in the EEPROM; And in the range of control that whether its data message of judgement is requiring earlier before CAN carries out information transfer; For example data are invalid, then stop the information transfer of CAN, start preparatory stop scheme.
4.SOCKET MODEM module bonded assembly remote monitor and control district can realize remote monitor and control, the failure message that CAN is transmitted is transferred to remote control center, and sends warning according to unusual data to monitoring center, and monitoring and control centre is made corresponding reaction then.
Fig. 4 is the monitoring scheme drawing of trans-regional elevator group controlling device.Its monitor mode and Fig. 3 are similar, and difference is that the object of its monitoring is respectively to the high trizonal transregional monitoring of carrying out with ladder in low, and each zone is arranged one to a plurality of transregional with ladder according to magnitude of traffic flow situation.
What Fig. 5 provided is the diagram of circuit of remote monitor and control.The semaphore that single terraced controller can directly be measured each elevator or the signal of analog quantity are gathered; Give cluster control unit through the CAN bus with data transmission; Trouble diagnosing parameter and the data deposited by the eeprom memory that extends out are sent to remote control center through the SOCKETMODEM module; Remote monitoring can be handled general fault, can come reheat treatment through on site maintenance if handled not.
Claims (5)
1. one kind is applied to dwelling house or the multiduty floor elevator prioritization scheme of handling official business, and it comprises the allocation of elevators of floor subregion, and the team control transit mode recognition methods of subregion and elevator monitoring realize that its characteristic has:
1) according to floor distribution and purposes skyscraper is carried out the zone division; Be divided into the several separate subregion; The interregional transregional interlayer marquis room that is provided with; The arrangement of transregional interlayer marquis room generally is located at the maximum layer floor in zone below it, is convenient to like this get into another zone from a zone, realizes trans-regional traffic;
2) passenger's magnitude of traffic flow in building is divided; Be divided into different transit modes; Be respectively: interlayer passenger flow pattern, trans-regional interlayer passenger flow pattern, idle pulley in up commuter rush hour pattern, descending commuter rush hour pattern, the zone; Adopt fuzzy neural network that the characteristic of the magnitude of traffic flow is discerned then, for further the subregion elevator being dispatched;
3) by cluster control unit the running condition of each elevator is controlled and had a warning function; This system comprises: based on cluster control unit, trans-regional cluster control unit, electric life controller in the Embedded zone, CAN bus communication module, SOCKET MODEN communication module and monitoring and control centre.
2. according to claim 1ly be used for dwelling house or handle official business multiduty floor elevator prioritization scheme; Its characteristics are; We to its be divided into low in Senior Three regional, perhaps two to four zones, special lift is launched in each zone; Launch corresponding low speed and express elevator according to high different height in low, the special lift in each zone only uses between the internal layer of one's respective area.
3. according to claim 1ly be used for dwelling house or the multiduty floor elevator prioritization scheme of handling official business, its characteristics are, in order to realize trans-regional interfloor traffic; Each zone also be respectively equipped with transregional with ladder to satisfy passenger demand, the passenger can get into transregional interlayer marquis room and exhale the Room, arrives the zone want then; What mention certainly is transregional first function with ladder; At this need annotatedly be, second function of trans-regional elevator be the interim elevator when being used for heavy traffic, such as; Be responsible for passenger's conveying of peak load conditions sooner or later, this point can remedy the weakness of the emergency capability shortcoming of common subregion elevator.
4. according to claim 1ly be used for dwelling house or handle official business multiduty floor elevator prioritization scheme; Its characteristics are; Before adopting fuzzy neural network that the characteristic of the magnitude of traffic flow is discerned, interfloor traffic is divided into interlayer passenger flow pattern and trans-regional interlayer passenger flow pattern in the zone, for the multiduty floor elevator of office; Be characterized in to carry out the feature identification of the fuzzy neural network magnitude of traffic flow for interlayer passenger flow pattern and trans-regional interlayer passenger flow pattern in the zone; If uptown floor situation; We are just passable with regard to the identification that only needs the interior interlayer passenger flow pattern in zone is carried out fuzzy neural network; This is that trans-regional interlayer flow is just very little, so do not need INTELLIGENT IDENTIFICATION because the dwelling house resident is generally little for trans-regional interfloor traffic demand.
5. according to claim 1ly be used for dwelling house or handle official business multiduty floor elevator prioritization scheme; Its characteristics are; Cluster control unit is monitored the running condition of each elevator; Because each regional special lift only uses between regional internal layer, so cluster control unit is only to the control of the special lift in the zone in the zone, same trans-regional cluster control unit is only controlled with elevator transregional.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103072856A (en) * | 2013-01-31 | 2013-05-01 | 哈尔滨工业大学 | Elevator-waiting people recognizing device based on infrared sensor and elevator scheduling method based on people recognition |
| CN110095994A (en) * | 2019-03-05 | 2019-08-06 | 永大电梯设备（中国）有限公司 | A kind of elevator multiplies a traffic flow-generator and multiplies the method that a traffic flow-generator automatically generates passenger flow data based on the elevator |
| CN110796580A (en) * | 2020-01-03 | 2020-02-14 | 中科寒武纪科技股份有限公司 | Intelligent traffic system management method and related products |
| CN111275966A (en) * | 2020-01-21 | 2020-06-12 | 西南交通大学 | Traffic mode identification method based on GPS speed information |
| CN116588776A (en) * | 2023-07-19 | 2023-08-15 | 常熟理工学院 | Elevator passenger flow prediction and optimal scheduling method and system |
| CN116823327A (en) * | 2023-06-22 | 2023-09-29 | 青岛中沃兴牧食品科技有限公司 | Prediction method for sales volume of pork monopoly network based on deep learning |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN103072856A (en) * | 2013-01-31 | 2013-05-01 | 哈尔滨工业大学 | Elevator-waiting people recognizing device based on infrared sensor and elevator scheduling method based on people recognition |
| CN110095994A (en) * | 2019-03-05 | 2019-08-06 | 永大电梯设备（中国）有限公司 | A kind of elevator multiplies a traffic flow-generator and multiplies the method that a traffic flow-generator automatically generates passenger flow data based on the elevator |
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| CN116823327A (en) * | 2023-06-22 | 2023-09-29 | 青岛中沃兴牧食品科技有限公司 | Prediction method for sales volume of pork monopoly network based on deep learning |
| CN116823327B (en) * | 2023-06-22 | 2024-04-02 | 青岛中沃兴牧食品科技有限公司 | Prediction method for sales volume of pork monopoly network based on deep learning |
| CN116588776A (en) * | 2023-07-19 | 2023-08-15 | 常熟理工学院 | Elevator passenger flow prediction and optimal scheduling method and system |
| CN116588776B (en) * | 2023-07-19 | 2023-11-03 | 常熟理工学院 | Elevator passenger flow prediction and optimal scheduling method and system |
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Application publication date: 20120711 |