CN110114294A - Recovery system - Google Patents
Recovery system Download PDFInfo
- Publication number
- CN110114294A CN110114294A CN201680091326.7A CN201680091326A CN110114294A CN 110114294 A CN110114294 A CN 110114294A CN 201680091326 A CN201680091326 A CN 201680091326A CN 110114294 A CN110114294 A CN 110114294A
- Authority
- CN
- China
- Prior art keywords
- unit
- recovery system
- classifier
- content
- lift appliance
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B5/00—Applications of checking, fault-correcting, or safety devices in elevators
- B66B5/0006—Monitoring devices or performance analysers
- B66B5/0018—Devices monitoring the operating condition of the elevator system
- B66B5/0025—Devices monitoring the operating condition of the elevator system for maintenance or repair
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B5/00—Applications of checking, fault-correcting, or safety devices in elevators
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/18—Status alarms
Landscapes
- Business, Economics & Management (AREA)
- Emergency Management (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Maintenance And Inspection Apparatuses For Elevators (AREA)
- Indicating And Signalling Devices For Elevators (AREA)
- Selective Calling Equipment (AREA)
Abstract
Classifier (11) classifies to the time series data inputted and exports multiple estimation defect contents.Classifier (13) classifies to the attribute data inputted and exports multiple estimation defect contents.The estimation defect content of estimation defect content and classifier (13) that failure determining section (14) is exported according to classifier (11) output determines defect content that lift appliance is occurred.Operation determining section (15) determines the job content for the defect content determined for failure determining section (14).
Description
Technical field
The present invention relates to a kind of recovery systems.
Background technique
A kind of system for after earthquake occurs restoring remotely lift appliance is described in patent document 1.?
In system documented by patent document 1, when the operating of lift appliance stops due to earthquake, is sent to administrative center and fortune is shown
Turn stopped signal and the signal of car status is shown.In administrative center, the signal received is shown over the display.Pipe
The manager at reason center sees the content shown on display, sends the signal for resetting earthquake detector.
Existing technical literature
Patent document
Patent document 1: Japanese Unexamined Patent Publication 2007-254039 bulletin
Summary of the invention
Subject to be solved by the invention
Patent document 1 discloses a kind of for making due to earthquake and the system of lift appliance out of service recovery.It is transporting
Turn due to earthquake and in the case where stopping, the case where there is no failures in lift appliance is more.Therefore, by visiting earthquake
It surveys device to reset, simply lift appliance can be made to restore.
On the other hand, it breaks down in lift appliance.In the case where failure has occurred in lift appliance, need carry out with
The corresponding operation of the failure occurred.In the past, when lift appliance breaks down, job content appropriate can not be grasped, thus
Remotely lift appliance can not be made to restore.
The present invention is completed to solve project as described above.The purpose of the present invention is to provide one kind in elevator
Device can determine the recovery system of job content appropriate for failure occurred in the case where failure has occurred.
Means for solving the problems
Recovery system of the invention has: receiving unit, receives time series data from lift appliance；1st classifier, quilt
The time series data that input receiving unit receives, and classify to the time series data inputted, it exports in multiple estimation failures
Hold；Acquisition unit obtains attribute data relevant to lift appliance；2nd classifier is entered the category of acquisition unit acquirement
Property data, classify to the attribute data inputted, export multiple estimation defect contents；Failure determination unit, according to the 1st
The estimation defect content that the estimation defect content and the 2nd classifier of classifier output export determines what lift appliance was occurred
Defect content；And job determination unit, determine the job content for the defect content determined for failure determination unit.
Recovery system of the invention has: storage unit, is stored with multiple defect contents, multiple job contents and needle
The probability of each job content is selected each defect content；Receiving unit receives time series data from lift appliance；The
1 classifier is entered the time series data that receiving unit receives, classifies to the time series data inputted, output is directed to
The estimation probability of happening for each defect content being stored in a storage unit；Acquisition unit obtains relevant to lift appliance
Attribute data；2nd classifier, is entered the attribute data of acquisition unit acquirement, and divides the attribute data inputted
Class, estimation probability of happening of the output for each defect content being stored in a storage unit；And determination unit, according to
The estimation probability of happening and be stored in a storage unit general that estimation probability of happening, the 2nd classifier of 1 classifier output export
Rate determines one from the job content being stored in a storage unit.
Invention effect
In recovery system of the invention, for example, according to the estimation defect content of the 1st classifier output and the 2nd classification
The estimation defect content of device output determines defect content that lift appliance is occurred.In addition, determining for the failure determined
The job content of content.It, then, can be true in the case where failure has occurred in lift appliance if it is recovery system of the invention
The fixed job content appropriate for failure occurred.
Detailed description of the invention
Fig. 1 is the exemplary figure for showing the recovery system in embodiments of the present invention 1.
Fig. 2 is the exemplary figure for showing administrative center.
Fig. 3 is the flow chart for showing the action example of the recovery system in embodiments of the present invention 1.
Fig. 4 is the flow chart for showing another action example of the recovery system in embodiments of the present invention 1.
Fig. 5 is another exemplary figure for showing administrative center.
Fig. 6 is the flow chart for showing another action example of the recovery system in embodiments of the present invention 1.
Fig. 7 is the exemplary figure for showing decision tree.
Fig. 8 is the exemplary figure for showing administrative center.
Fig. 9 is the flow chart for showing the action example of the recovery system in embodiments of the present invention 2.
Figure 10 is the figure for showing the hardware configuration of administrative center.
Specific embodiment
Referring to attached drawing, the present invention will be described.Suitably simplify or the repetitive description thereof will be omitted.In the various figures, identical label
Indicate identical part or comparable part.
Embodiment 1.
Fig. 1 is the exemplary figure for showing the recovery system in embodiments of the present invention 1.Administrative center 1 can with it is long-range
Multiple elevator device communicated.Each lift appliance for example has carriage 2 and counterweight 3.Carriage 2 and counterweight 3 are hanged by main rope 4
It is hung in hoistway.Traction machine for example has driving rope sheave 5 and motor 6.Around hanging with main rope 4 on driving rope sheave 5.Drive rope sheave
5 are driven by motor 6.Motor 6 is controlled by control device 7.Control device 7 is connect with communication device 8.Communication device 8 and outer
The equipment in portion is communicated.Each lift appliance is communicated by communication device 8 with administrative center 1.
When lift appliance breaks down, is obtained by communication device 8 and the snapshot of the signal value of state of elevator is shown, is tracked
Data.Tracking data is an example of the signal group comprising multiple signals.For example, comprising for determining that elevator fills in tracking data
Set the signal of itself.It include the signal for showing the moment in tracking data.It include the electricity for showing control device 7 in tracking data
The signal of flow valuve and voltage value.Comprising showing the speed of motor 6 and the signal of torque in tracking data.In tracking data
Signal comprising showing the position of carriage 2.The signal for including in tracking data is not limited to these examples.Illustrated by signal one
Part can also be not included in tracking data.It also may include other signals in tracking data.
When lift appliance breaks down, the stipulated time that for failure front and back occurs for communication device 8 obtains tracking data.
For example, communication device 8 is directed to the phase that 50ms after preceding 50ms occurs to failure occurs from failure when lift appliance breaks down
Between, obtain the tracking data of every 5ms.Communication device 8 is sent to pipe when achieving tracking data, by acquired tracking data
Reason center 1.
In addition, communication device 8 is when lift appliance breaks down, by diagnostic code and acquired one starting of tracking data
Give administrative center 1.It include the data for showing failure cause in diagnostic code.
Fig. 2 is the exemplary figure for showing administrative center 1.Administrative center 1 has such as storage unit 9, receiving unit 10, classifier
11, acquisition unit 12, classifier 13, failure determining section 14, operation determining section 15, determination unit 16, transmission unit 17 and notice control
Portion 18.Hereinafter, also referring to Fig. 3, the function and movement of this recovery system are illustrated.Fig. 3 is to show embodiment party of the invention
The flow chart of the action example of recovery system in formula 1.
When arbitrary lift appliance breaks down, tracking is sent from the communication device 8 of the lift appliance to administrative center 1
Data and diagnostic code.The data sent from communication device 8 receive (S101) by receiving unit 10 in administrative center 1.When by receiving
When portion 10 receives from the data of communication device 8, in administrative center 1, determined whether for the data received etc.
Time series data (S102).
The defect content estimated according to the data output inputted of classifier 11.Time series data is input into classifier
11.It include multiple time series datas in the received tracking data of receiving unit 10.For example, showing the signal of the current value of control device 7
Transition be time series data.The transition for showing the signal of the speed of motor 6 are time series datas.That is, receiving unit 10 is from elevator
Device receives an example of the unit of time series data.It is in the data that receiving unit 10 receives in S101, be determined in S102
Classifier 11 is input into for the data of time series data.
11 pairs of time series datas inputted of classifier are classified (S103), are estimated defect content (S104).Classifier 11
Multiple estimation defect contents are exported according to classification results.Estimate that can also be had from the estimation defect content that classifier 11 exports
The additional informations such as the probability of happening for the failure counted out.
The defect content estimated according to the data output inputted of classifier 13.Attribute data is input into classifier
13.Attribute data be in data relevant to lift appliance be not time series data data.For example, diagnostic code is attribute number
According to.The data for showing the type of lift appliance are attribute datas.The data for showing normal speed are attribute datas.It is shown provided with
The data of the floor of the building of lift appliance are attribute datas.
Acquisition unit 12 obtains attribute data.Acquisition unit 12 takes when receiving unit 10 receives tracking data and diagnostic code
Obtain attribute data relevant to the lift appliance for sending the data.For example, the data that acquisition unit 12 is received from receiving unit 10
Middle acquirement attribute data.Acquisition unit 12 can also obtain attribute data from the data being stored in storage unit 9.The quilt in S102
It is determined as not being that the data of time series data are input into classifier 13.
13 pairs of attribute datas inputted of classifier are classified (S105), are estimated defect content (S106).Classifier 13
Multiple estimation defect contents are exported according to classification results.Estimate that can also be had from the estimation defect content that classifier 13 exports
The additional informations such as the probability of happening for the failure counted out.
Failure determining section 14 determines the defect content (S107) that lift appliance is occurred.Failure determining section 14 for example according to from
The estimation defect content and the above-mentioned determination of estimation defect content progress exported from classifier 13 that classifier 11 exports.For example, such as
Fruit exports from the highest estimation defect content of probability of happening in the estimation defect content that classifier 11 exports and from classifier 13
Estimation defect content in the highest estimation defect content of probability of happening it is identical, then failure determining section 14 will be in the estimation failure
Appearance is determined as the defect content that lift appliance is occurred.Failure determining section 14 can also be according to the generation multiplied by estimation defect content
Value obtained from probability etc. determines a defect content.
Operation determining section 15 determines the job content (S108) for the defect content determined by failure determining section 14.Example
Such as, the job content that should be selected is preset for each defect content that failure determining section 14 can determine.Above-mentioned setting content
Such as it is stored in storage unit 9.As long as operation determining section 15 is determined referring to the setting content being stored in storage unit 9 is directed to event
Hinder the job content of content.
Determination unit 16 determines that can the job content that determined by operation determining section 15 be implemented by remotely operating
(S109).For example, being determined as in S109 when job content as " reset of lift appliance " has been determined in S108
"Yes".When by determination unit 16 be determined as can be by remotely operating to implement when, transmission unit 17 will be used to make operation determining section 15
The instruction for implementing the job content determined in S108 is sent to the lift appliance (S110) that failure has occurred.
On the other hand, when " replacement substrate " such job content for needing to send maintenance personnel has been determined in S108
When, "No" is determined as in S109.By determination unit 16 be determined as cannot be by remotely operating to implement in the case where, for example,
Notice control unit 18 makes the job content (S111) for notifying operation determining section 15 to determine in S108 from notifying device 22.Notice control
Portion 18 processed can also lead to the result that determination unit 16 determines in S109 together with above-mentioned job content from notifying device 22
Know.When by determination unit 16 be determined as can be by remotely operating to implement when, notice control unit 18 can also make from notifying device 22
The result that the job content and determination unit 16 that notice operation determining section 15 is determined in S108 determine in S109.Notifying device
22 are for example arranged in administrative center 1.
If it is example shown in present embodiment, then in the case where failure has occurred in lift appliance, it can determine needle
To the job content appropriate of the failure occurred.In particular, in the example shown in present embodiment, according to time series data
Estimation defect content obtained from estimating defect content obtained from being classified and classifying to attribute data is made to determine
Hold in the industry.Due to realizing classification by using multiple classifiers of independent data for same event, can be improved really
Determine the reliability of result.
In the example depicted in fig. 3, in S110, the instruction for implementing job content is sent automatically.This is an example.?
In the case where being determined as "Yes" in S109, notifying device 22 can also be made to notify operation true without the automatic transmission of instruction
Determine the job content that portion 15 determines in S108 and the result that determination unit 16 determines in S109.In this case, root
The instruction for implementing job content is sent according to the judgement of manager.
In the example depicted in fig. 3, in S109, determine that can the job content that determined by operation determining section 15 pass through
Remote operation is to implement.This is an example.It can also make notifying device after the processing for carrying out S108 without above-mentioned judgement
The job content that 22 notice operation determining sections 15 are determined in S108.In this case, made in the industry by manager
Hold the judgement that can implement by remotely operating.
Fig. 4 is the flow chart for showing another action example of the recovery system in embodiments of the present invention 1.Fig. 4 shows Fig. 3
S109 shown in processing concrete example.Determination unit 16 can also according to the time series data that receiving unit 10 receives in S101 come
Determine that can the job content that determined by operation determining section 15 be implemented by remotely operating.
For example, determination unit 16, according to the signal for showing weighing value for including in tracking data, failure is having occurred in judgement
Whether someone takes (S201) in the carriage 2 of lift appliance.If someone takes in carriage 2, determination unit 16 be determined as by
The job content that operation determining section 15 is determined can not be implemented by remotely operating.Determination unit 16 can also be according to tracking number
Whether the signal for including in is normal (S202) to sentence main rope 4.If exception has occurred in main rope 4, determination unit 16 determines
Job content to be determined by operation determining section 15 cannot be implemented by remotely operating.
Determination unit 16 can also determine the braking for making to drive rope sheave 5 static according to the signal for including in tracking data
Whether device is normal (S203).If exception has occurred in brake, what determination unit 16 was judged to being determined by operation determining section 15
Job content cannot be implemented by remotely operating.Critical item shown in S201 to S203 is an example.It can be only with S201
It one into critical item shown in S203, can also use multiple.Also it can according to need using other critical items.Example
Such as, the time series data that determination unit 16 is received not only according to receiving unit 10, the attribute data that can also be obtained according to acquisition unit 12
To determine that can the job content that determined by operation determining section 15 be implemented by remotely operating.It is used when 16 Duis of determination unit
Whole critical items when being determined as "Yes", transmission unit 17 is sent to the lift appliance that failure has occurred for making to apply industry in fact
The instruction (S110) for the job content that determining section 15 is determined in S108.
Fig. 5 is another figure for showing administrative center 1.In the example depicted in fig. 5, administrative center 1 is in addition to having Fig. 2
Shown in except each element, be also equipped with update section 19 and update section 20.Update section 19 updates classifier 11.Update section 20, which updates, divides
Class device 13.Hereinafter, also referring to Fig. 6 and Fig. 7, the function and movement of update section 19 and update section 20 are illustrated.Fig. 6 is to show
The flow chart of another action example of recovery system in embodiments of the present invention 1.
When any lift appliance breaks down, tracking number is sent from the communication device 8 of the lift appliance to administrative center 1
According to and diagnostic code.The data sent from communication device 8 receive (S301) by receiving unit 10 in administrative center 1.By receiving unit 10
The data received are stored in storage unit 9.
The data received from multiple elevator device are stored in storage unit 9.In addition, being also stored in storage unit 9
Other data relevant to lift appliance.For example, be stored in storage unit 9 in the lift appliance that failure has occurred specifically into
Capable job content.The job content has e.g. actually carried out the data that the maintenance personnel of operation inputs after operation.It is depositing
The specific defect content that maintenance personnel judges can also be stored in storage portion 9.The defect content is actually to have carried out operation
The data that are inputted after operation of maintenance personnel.As another example, type, the volume of each lift appliance are stored in storage unit 9
The data such as constant speed degree and normal speed.The number of floor for being provided with the building of each lift appliance etc. is stored in storage unit 9
According to.Update section 19 and update section 20 are updated processing according to these data being stored in storage unit 9.
Update section 19 is for example learnt (S303) based on receiving unit 10 from the time series data that each lift appliance receives, and
It updates classifier 11 (S304).The processing of S302 is identical as the processing of S102 shown in Fig. 3.Ordinal number when being judged as in S302
According to data be input into update section 19.
The method that update section 19 updates classifier 11 can be any method.For example, about time series data, it will be for M
There are [x as time series data for each of signal1, x2..., xM]TAs the input to update section 19.Here, []TIt indicates
Transposition.Update section 19 for example carries out the supervision of the data inputted after operation based on maintenance personnel using neural network (NN)
It practises.
Update section 20 is for example learnt (S305) based on attribute data relevant to each lift appliance, and updates classifier
13(S306).It is judged as not being that the data of time series data are input into update section 20 in S302.
The method that update section 20 updates classifier 13 can be any method.For example, following table 1, which is shown, is stored in storage unit
The example of attribute data in 9.Update section 20 generates decision tree as shown in Figure 7 for example to be learnt.Fig. 7 is to show decision
The exemplary figure of tree.In addition, the learning method of update section 20 is not limited to the learning method based on decision tree.For example, as update
The study in portion 20, can also be using the methods of mode excavation.
[table 1]
| Normal speed | Rated capacity | ··· | Diagnostic code | Defect content (maintenance personnel's input) |
| 100m/min | 1500kg | ··· | 0001 | B1 failure |
| 200m/min | 2000kg | ··· | 0001 | B2 failure |
| 150m/min | 1800kg | ··· | 0101 | B3 failure |
| : | : | : | : | : |
| 800m/min | 2500kg | ··· | 1111 | Bn failure |
If it is Fig. 5 and example shown in fig. 6, for same event, each classifier is carried out to have used independent data
Study, therefore can be improved the reliability of definitive result.
Embodiment 2.
The example of recovery system in present embodiment is identical as example shown in FIG. 1.Fig. 8 shows administrative center 1
Exemplary figure.In the example shown in present embodiment, administrative center 1 have for example storage unit 9, receiving unit 10, classifier 11,
Acquisition unit 12, classifier 13, determining section 21, determination unit 16, transmission unit 17 and notice control unit 18.
Such as error listing, the job list and list of probabilities are stored in storage unit 9.Table 2 shows error listing
Example.It include the multiple defect contents that may occur in lift appliance in error listing.
[table 2]
| Number | Defect content |
| 1 | B1 failure |
| 2 | B2 failure |
| : | |
| n | Bn failure |
Table 3 shows the example of the job list.In the job list comprising can in the lift appliance that failure has occurred into
Capable multiple job contents.
[table 3]
| Number | Defect content (maintenance personnel's input) |
| 1 | OP1 operation |
| 2 | OP2 operation |
| : | |
| k | OPk operation |
Table 4 shows the example of list of probabilities.Comprising in the every failure for including in error listing in list of probabilities
Hold the probability for the every job content for including in selection the job list.
[table 4]
Hereinafter, also referring to Fig. 9, the function and movement of this recovery system are illustrated.Fig. 9 is to show implementation of the invention
The flow chart of the action example of recovery system in mode 2.
When arbitrary lift appliance breaks down, tracking is sent from the communication device 8 of the lift appliance to administrative center 1
Data and diagnostic code.The data sent from communication device 8 receive (S401) by receiving unit 10 in administrative center 1.When by receiving
When portion 10 receives from the data of communication device 8, in administrative center 1, determined whether for the data received etc.
Time series data (S402).
In the present embodiment, classifier 11 is according to the data inputted, and output is for the items for including in error listing
The estimation probability of happening of defect content.For example, being input into classifier 11 by the time series data that receiving unit 10 receives.Classifier
11 pairs of time series datas inputted are classified (S403), are estimated probability of happening (S404).Classifier 11 is defeated according to classification results
Out for the estimation probability of happening P of every defect contentu(xi).Wherein, xiIt is in i-th of the failure recorded in error listing
Hold.
In addition, classifier 13 is according to the data inputted, output is for the every defect content for including in error listing
Estimate probability of happening.For example, being input into classifier 13 by the attribute data that acquisition unit 12 obtains.13 pairs of classifier are inputted
Attribute data is classified (S405), is estimated probability of happening (S406).Classifier 13 is according to classification results, and output is for every event
Hinder the estimation probability of happening P of contentv(xi)。
Determining section 21 determines one (S408) from the job content for including in the job list.Determining section 21 is according to from classification
The estimation probability of happening of the output of device 11, the probability for including from the estimation probability of happening and list of probabilities that classifier 13 exports come
Carry out above-mentioned determination.For example, setting the estimation probability of happening P exported from classifier 11u(xi) with the probability phase that includes in list of probabilities
The multiplied result arrived is Pu(xi)P(xi|zj).If the estimation probability of happening P exported from classifier 11v(xi) with wrapped in list of probabilities
The result that the probability multiplication contained obtains is Pv(xi)P(xi|zj).Wherein, zjIt is that i-th recorded in the job list is made in the industry
Hold.Determining section 21 for example selects Pu(xi)P(xi|zj) and Pv(xi)P(xi|zj) the highest job content of average value.
Determination unit 16 determines that can the job content that determined by determining section 21 be implemented (S409) by remotely operating.When
By determination unit 16 be determined as can be by remotely operating to implement when, transmission unit 17 to have occurred failure lift appliance send use
In the instruction (S410) for making it implement the job content that determining section 21 is determined in S408.
On the other hand, by determination unit 16 be determined as cannot be by remotely operating to implement in the case where, for example, notice control
Portion 18 processed makes the job content (S411) for notifying determining section 21 to determine in S408 from notifying device 22.Notify that control unit 18 can also
It is notified together with above-mentioned job content from notifying device 22 with the result for determining determination unit 16 in S409.When by determination unit 16
It is determined as when can be by remotely operating to implement, notice control unit 18 can also make to notify determining section 21 to exist from notifying device 22
The result that the job content and determination unit 16 determined in S408 determine in S409.
If it is example shown in present embodiment, then in the case where failure has occurred in lift appliance, it can determine needle
To the job content appropriate of the failure occurred.In particular, in the example shown in present embodiment, according to time series data
Estimation probability of happening obtained from estimating probability of happening obtained from being classified and classifying to attribute data is made to determine
Hold in the industry.Due to the classification for realize by using multiple classifiers of independent data for same event, can mention
The reliability of high definitive result.
In the example depicted in fig. 9, in S410, the instruction for implementing job content is sent automatically.This is an example.?
In the case where being determined as "Yes" in S409, it can also make to notify to determine from notifying device 22 without the automatic transmission of instruction
The result that the job content and determination unit 16 that portion 21 determines in S408 determine in S409.In this case, according to
The judgement of manager is to send the instruction for implementing job content.
In the example depicted in fig. 9, in S409, determine that can the job content that determined by determining section 21 by long-range
Operation is to implement.This is an example.It can also make after the processing for carrying out S408 without above-mentioned judgement from notifying device 22
The job content that notice determining section 21 is determined in S408.In this case, can carry out job content by manager
The judgement implemented by remotely operating.
Also the same in the example shown in present embodiment, determination unit 16 can receive in S401 according to receiving unit 10
Time series data determine that can the job content that determined by determining section 21 be implemented by remotely operating.That is, can also adopt
With action example shown in Fig. 4.In addition, the time series data that determination unit 16 can not only be received according to receiving unit 10, it can be with root
Determine that can the job content that determined by determining section 21 by remotely operating come real according to the attribute data that acquisition unit 12 obtains
It applies.
In addition, administrative center 1 other than having each element shown in Fig. 8, can also be also equipped with update section 19 and update
Portion 20.Update section 19 is for example learnt based on receiving unit 10 from the time series data that each lift appliance receives, and updates classification
Device 11.The method that update section 19 updates classifier 11 can be any method.Update section 19 for example using neural network (NN) come
Carry out the supervised learning of the data inputted after operation based on maintenance personnel.Update section 20 is for example based on related to each lift appliance
Attribute data learnt, and update classifier 13.The method that update section 20 updates classifier 13 can be any method.More
New portion 20 generates decision tree for example to be learnt.
Each element shown in label 9~21 indicates the function that administrative center 1 has.Figure 10 is show administrative center 1 hard
The figure of part structure.As hardware resource, administrative center 1 for example has the processing circuit comprising processor 23 and memory 24.It deposits
The function that storage portion 9 has is realized by memory 24.Administrative center 1 is by being stored in memory by the execution of processor 23
Program in 24 realizes the function in each portion shown in label 10~21.
Processor 23 is also referred to as CPU (Central Processing Unit: central processing unit), central processing dress
It sets, processing unit, arithmetic unit, microprocessor, microcomputer or DSP.As memory 24, can also be deposited using semiconductor
Reservoir, disk, floppy disk, CD, compact disk, mini-disk or DVD.Adoptable semiconductor memory includes RAM, ROM, sudden strain of a muscle
Deposit memory, EPROM and EEPROM etc..
Part or all of each function possessed by administrative center 1 can also be realized by hardware.It is managed as realizing
The hardware of the function at reason center 1, can also using single circuit, compound circuit, programmed process device, multiple programming processor,
ASIC, FPGA or their combination.
Industrial availability
The system that recovery system of the invention can be suitable for be communicated with lift appliance.
Label declaration
1: administrative center；2: carriage；3: counterweight；4: main rope；5: driving rope sheave；6: motor；7: control device；8: logical
T unit；9: storage unit；10: receiving unit；11: classifier；12: acquisition unit；13: classifier；14: failure determining section；15: operation
Determining section；16: determination unit；17: transmission unit；18: notice control unit；19: update section；20: update section；21: determining section；22: logical
Know device；23: processor；24: memory.
Claims (10)
1. a kind of recovery system, wherein the recovery system has:
Receiving unit receives time series data from lift appliance；
1st classifier is entered the time series data that the receiving unit receives, and divides the time series data inputted
Class exports multiple estimation defect contents；
Acquisition unit obtains attribute data relevant to the lift appliance；
2nd classifier is entered the attribute data that the acquisition unit obtains, and divides the attribute data inputted
Class exports multiple estimation defect contents；
Failure determination unit is exported according to the estimation defect content of the 1st classifier output and the 2nd classifier
Estimation defect content determines defect content that the lift appliance is occurred；And
Job determination unit determines the job content for the defect content determined for the failure determination unit.
2. recovery system according to claim 1, wherein
The recovery system is also equipped with judging unit, which determines the job content energy that the job determination unit is determined
It is no to be implemented by remotely operating.
3. recovery system according to claim 2, wherein
The recovery system is also equipped with transmission unit, when by the judging unit be determined as can be by remotely operating to implement when,
The transmission unit is sent to the lift appliance for making the lift appliance implement the work that the job determination unit is determined
The instruction held in the industry.
4. a kind of recovery system, wherein the recovery system has:
Storage unit is stored with multiple defect contents, multiple job contents and has selected respectively for each defect content
The probability of a job content；
Receiving unit receives time series data from lift appliance；
1st classifier is entered the time series data that the receiving unit receives, and divides the time series data inputted
Class, estimation probability of happening of the output for each defect content being stored in the storage unit；
Acquisition unit obtains attribute data relevant to the lift appliance；
2nd classifier is entered the attribute data that the acquisition unit obtains, and divides the attribute data inputted
Class, estimation probability of happening of the output for each defect content being stored in the storage unit；And
Determination unit is sent out according to the estimation of the estimation probability of happening of the 1st classifier output, the 2nd classifier output
Raw probability and the probability being stored in the storage unit, determine one from the job content being stored in the storage unit
It is a.
5. recovery system according to claim 4, wherein
The recovery system is also equipped with judging unit, which determines that can the job content that the determination unit is determined lead to
Remote operation is crossed to implement.
6. recovery system according to claim 5, wherein
The recovery system is also equipped with transmission unit, when by the judging unit be determined as can be by remotely operating to implement when,
The transmission unit is sent to the lift appliance for making the lift appliance implement work that the determination unit is determined in the industry
The instruction of appearance.
7. recovery system according to claim 2 or 5, wherein
The judging unit determines that can job content by remotely grasping according to the time series data that the receiving unit receives
Make to implement.
8. recovery system according to claim 2 or 5, wherein
The attribute data that the time series data and the acquisition unit that the judging unit is received according to the receiving unit obtain
To determine that can job content be implemented by remotely operating.
9. recovery system according to claim 2 or 5, wherein
The recovery system is also equipped with notice control unit, which makes that the judging unit is notified to determine by notifying device
Result out.
10. according to claim 1 to recovery system described in any one of 9, wherein the recovery system is also equipped with:
1st updating unit carries out the study of the time series data received based on the receiving unit, to the 1st classifier
It is updated；And
2nd updating unit carries out the study based on attribute data relevant to lift appliance, carries out to the 2nd classifier
It updates.
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| PCT/JP2016/088706 WO2018122921A1 (en) | 2016-12-26 | 2016-12-26 | Recovery system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110114294A true CN110114294A (en) | 2019-08-09 |
| CN110114294B CN110114294B (en) | 2020-11-03 |
Family
ID=62707201
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201680091326.7A Active CN110114294B (en) | 2016-12-26 | 2016-12-26 | Recovery system |
Country Status (4)
| Country | Link |
|---|---|
| JP (1) | JP6693576B2 (en) |
| KR (1) | KR102238386B1 (en) |
| CN (1) | CN110114294B (en) |
| WO (1) | WO2018122921A1 (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114728759B (en) * | 2019-11-20 | 2023-02-28 | 三菱电机楼宇解决方案株式会社 | Determination device, determination method, and computer-readable recording medium |
Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| BE886861A (en) * | 1979-12-28 | 1981-06-24 | Westinghouse Electric Corp | ELEVATOR INSTALLATION |
| JPH06271240A (en) * | 1993-03-24 | 1994-09-27 | Hitachi Building Syst Eng & Service Co Ltd | Trouble diagnostic device for elevator |
| JP2004133553A (en) * | 2002-10-08 | 2004-04-30 | Toshiba Corp | Diagnostic device for equipment |
| JP2007254039A (en) * | 2006-03-20 | 2007-10-04 | Toshiba Elevator Co Ltd | Restoration system for elevator |
| US20090218178A1 (en) * | 2005-07-18 | 2009-09-03 | Lence-Barreiro Juan A | Remotely Performed and/or Assisted Restoration of Elevator Service |
| CN102765643A (en) * | 2012-05-31 | 2012-11-07 | 天津大学 | Elevator fault diagnosis and early-warning method based on data drive |
| CN102923538A (en) * | 2012-07-06 | 2013-02-13 | 天津大学 | Elevator health management and maintenance system based on Internet of things and collection and assessment method |
| CN101683946B (en) * | 2008-09-27 | 2013-07-10 | 三菱电机大楼技术服务株式会社 | Diagnosis operation device and method of elevator |
| CN103402900A (en) * | 2011-02-28 | 2013-11-20 | 三菱电机株式会社 | Device for detecting sway of elevator rope |
| CN104118782A (en) * | 2014-07-08 | 2014-10-29 | 广州日滨科技发展有限公司 | Elevator frequency converter bus capacitor capacity detection method and system and diagnosis early warning method and system |
| CN105173943A (en) * | 2015-08-10 | 2015-12-23 | 沈阳市蓝光自动化技术有限公司 | Elevator inspection system |
| CN105731209A (en) * | 2016-03-17 | 2016-07-06 | 天津大学 | Intelligent prediction, diagnosis and maintenance method for elevator faults on basis of Internet of Things |
| JP2016166069A (en) * | 2015-03-10 | 2016-09-15 | 東芝エレベータ株式会社 | Maintenance work support device, system and method for elevator |
| CN106219342A (en) * | 2016-08-19 | 2016-12-14 | 广州广日电梯工业有限公司 | Elevator self diagnosis based on time-frequency convert algorithm and pre-diagnostic system and method |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH092752A (en) * | 1995-06-20 | 1997-01-07 | Hitachi Building Syst Eng & Service Co Ltd | Elevator diagnosis device |
| JP3594769B2 (en) * | 1997-07-17 | 2004-12-02 | 株式会社日立ビルシステム | Remote monitoring device |
-
2016
- 2016-12-26 KR KR1020197017123A patent/KR102238386B1/en active IP Right Grant
- 2016-12-26 JP JP2018558535A patent/JP6693576B2/en not_active Expired - Fee Related
- 2016-12-26 CN CN201680091326.7A patent/CN110114294B/en active Active
- 2016-12-26 WO PCT/JP2016/088706 patent/WO2018122921A1/en active Application Filing
Patent Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| BE886861A (en) * | 1979-12-28 | 1981-06-24 | Westinghouse Electric Corp | ELEVATOR INSTALLATION |
| JPH06271240A (en) * | 1993-03-24 | 1994-09-27 | Hitachi Building Syst Eng & Service Co Ltd | Trouble diagnostic device for elevator |
| JP2004133553A (en) * | 2002-10-08 | 2004-04-30 | Toshiba Corp | Diagnostic device for equipment |
| US20090218178A1 (en) * | 2005-07-18 | 2009-09-03 | Lence-Barreiro Juan A | Remotely Performed and/or Assisted Restoration of Elevator Service |
| JP2007254039A (en) * | 2006-03-20 | 2007-10-04 | Toshiba Elevator Co Ltd | Restoration system for elevator |
| CN101683946B (en) * | 2008-09-27 | 2013-07-10 | 三菱电机大楼技术服务株式会社 | Diagnosis operation device and method of elevator |
| CN103402900A (en) * | 2011-02-28 | 2013-11-20 | 三菱电机株式会社 | Device for detecting sway of elevator rope |
| CN102765643A (en) * | 2012-05-31 | 2012-11-07 | 天津大学 | Elevator fault diagnosis and early-warning method based on data drive |
| CN102923538A (en) * | 2012-07-06 | 2013-02-13 | 天津大学 | Elevator health management and maintenance system based on Internet of things and collection and assessment method |
| CN104118782A (en) * | 2014-07-08 | 2014-10-29 | 广州日滨科技发展有限公司 | Elevator frequency converter bus capacitor capacity detection method and system and diagnosis early warning method and system |
| JP2016166069A (en) * | 2015-03-10 | 2016-09-15 | 東芝エレベータ株式会社 | Maintenance work support device, system and method for elevator |
| CN105173943A (en) * | 2015-08-10 | 2015-12-23 | 沈阳市蓝光自动化技术有限公司 | Elevator inspection system |
| CN105731209A (en) * | 2016-03-17 | 2016-07-06 | 天津大学 | Intelligent prediction, diagnosis and maintenance method for elevator faults on basis of Internet of Things |
| CN106219342A (en) * | 2016-08-19 | 2016-12-14 | 广州广日电梯工业有限公司 | Elevator self diagnosis based on time-frequency convert algorithm and pre-diagnostic system and method |
Also Published As
| Publication number | Publication date |
|---|---|
| JP6693576B2 (en) | 2020-05-13 |
| CN110114294B (en) | 2020-11-03 |
| KR20190077558A (en) | 2019-07-03 |
| WO2018122921A1 (en) | 2018-07-05 |
| KR102238386B1 (en) | 2021-04-09 |
| JPWO2018122921A1 (en) | 2019-10-31 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11425004B2 (en) | In-fabric traffic analysis | |
| CN109902721A (en) | Outlier detection model verification method, device, computer equipment and storage medium | |
| CN111392530A (en) | Robot, robot calling method, elevator control method and device | |
| CN111539610A (en) | Production management system, method, device, equipment and medium for assembly workshop | |
| EP2245515B1 (en) | Apparatus and method for alarm suppression in a monitoring system | |
| CN104627785B (en) | The method and configuration of condition monitoring for elevator rope | |
| JP2010222074A (en) | Elevator group supervisory operation system and method | |
| CN106276459A (en) | A kind of elevator rescue system based on Internet of Things and method | |
| CN107404540A (en) | The synchronous method and device of data | |
| JP2011144025A (en) | Group management apparatus for elevator | |
| CN109889512A (en) | A kind of method for detecting abnormality and device of charging pile CAN message | |
| US20180305175A1 (en) | Elevator management system | |
| CN110114294A (en) | Recovery system | |
| CN110121475A (en) | The Long-Range Surveillance Unit of elevator | |
| CN105084140A (en) | Optimization method and device for elevator calling and waiting time distributed at intervals in circulating manner | |
| CN108473273A (en) | Elevator data communication arrangement | |
| Luh et al. | Group elevator scheduling with advance information for normal and emergency modes | |
| CN110088022A (en) | Restore support system | |
| JP6766982B2 (en) | Elevator maintenance work support device | |
| JP7440395B2 (en) | Optimal solution search device and optimal solution search program | |
| CN110114295A (en) | The control device of elevator | |
| CN105490827B (en) | A kind of method and device obtaining network state | |
| CN113240287A (en) | Manufacturing service self-adaptive scheduling method based on supply and demand relationship | |
| CN109188269A (en) | Judge the method for electrical fault | |
| CN110035969A (en) | The remote recovery system of elevator faults |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CP01 | Change in the name or title of a patent holder | ||
| CP01 | Change in the name or title of a patent holder |
Address after: Tokyo, Japan Patentee after: MITSUBISHI ELECTRIC Corp. Patentee after: Mitsubishi Electric Building Solutions Co.,Ltd. Address before: Tokyo, Japan Patentee before: MITSUBISHI ELECTRIC Corp. Patentee before: MITSUBISHI ELECTRIC BUILDING TECHNO-SERVICE Co.,Ltd. |