CN107255969A - Endowment robot supervisory systems - Google Patents
Endowment robot supervisory systems Download PDFInfo
- Publication number
- CN107255969A CN107255969A CN201710508312.7A CN201710508312A CN107255969A CN 107255969 A CN107255969 A CN 107255969A CN 201710508312 A CN201710508312 A CN 201710508312A CN 107255969 A CN107255969 A CN 107255969A
- Authority
- CN
- China
- Prior art keywords
- self
- control instruction
- instruction
- module
- learning
- 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
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/04—Programme control other than numerical control, i.e. in sequence controllers or logic controllers
- G05B19/042—Programme control other than numerical control, i.e. in sequence controllers or logic controllers using digital processors
- G05B19/0428—Safety, monitoring
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/20—Pc systems
- G05B2219/24—Pc safety
- G05B2219/24024—Safety, surveillance
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Automation & Control Theory (AREA)
- Manipulator (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The present patent application discloses a kind of endowment robot supervisory systems, including self learning system, and the self learning system is used to carry out self-teaching to off-limits instruction, in addition to:Selftest module, selftest module is used to emulate Self-learning control instruction to judge whether Self-learning control instruction has logic error by analog simulator;Background monitoring module, background monitoring module is used for the Self-learning control instruction for receiving selftest module transmission, backstage technical staff judges after the corresponding user instruction of input whether Self-learning control instruction can make correct behavior reaction with control machine people by analogue simulation.This programme can carry out remote monitoring to endowment robot working condition, it is ensured that the normal work of robot, improve the interaction capabilities of endowment machine person to person.
Description
Technical field
The present invention relates to robot communication technical field, more particularly to a kind of endowment robot supervisory systems.
Background technology
With continuing to develop for robot automtion, behavior robot is increasingly valued by people, especially for
The endowment service humanoid robot of old user, because one-child family increasingly increases, children look after and accompanied the time of old man
It is limited, children can be substituted to a certain extent by the endowment service robot and solve the problem of the elderly shortage of staff takes care of.
Endowment service type robot behavior response rule is all worked out in advance when dispatching from the factory, and these are according to conventional day
Often the behavior reaction rule of summary of experience out is likely to not adapt to miscellaneous running environment, it is impossible to for the spy of user
Point and demand are interacted, it is impossible to preferably incorporate the life of people.With advances in technology, robot adds self study work(
Can, can continuous summing up experience, self-teaching in the process of running to off-limits instruction.
However, above-mentioned endowment robot can not be verified during self study to learning outcome, do not know final
Whether learning outcome is correct, and because endowment robot has accessed external network, there is assault and distort instruction situation, both
Will influence right instructions execution, and then influence the elderly to be interacted with robot of supporting parents.
The content of the invention
It is long-range to be carried out to endowment robot working condition the invention is intended to provide a kind of endowment robot supervisory systems
Monitoring, it is ensured that the normal work of robot, improves the interaction capabilities of endowment machine person to person.
The base case that the present invention is provided is:Endowment robot supervisory systems, including self learning system, the self study
System is used to carry out self-teaching to off-limits instruction, in addition to:
Selftest module, selftest module is used to emulate Self-learning control instruction to judge that Self-learning control is instructed by analog simulator
Whether logic error is had:
When judged result to there is logic error, then logic error result is fed back into self learning system, self learning system is learned again
Practise modification Self-learning control instruction;
When judged result is without logic error, then to send Self-learning control and instruct to next module;
Background monitoring module, background monitoring module is used for the Self-learning control instruction for receiving selftest module transmission, backstage technology people
Member judges after the corresponding user instruction of input whether Self-learning control instruction can be made with control machine people by analogue simulation
Correct behavior reaction:
If the behavior reaction made is correct, judges that Self-learning control instruction is correct, Self-learning control instruction is stored to machine
In the database of device people's control store instruction;
If the behavior reaction made is incorrect, Self-learning control instruction errors are judged, backstage technical staff is to self study control
Instruction processed is modified, and revised control instruction is stored into the database of control store instruction.
The operation principle of base case:Self learning system is carried out after self-teaching to off-limits instruction, by self study
The control instruction of completion is sent to selftest module, and selftest module emulates Self-learning control instruction to judge certainly by analog simulator
Whether study control instruction has logic error:
When judged result to there is logic error, then logic error result is fed back into self learning system, self learning system is learned again
Practise modification Self-learning control instruction;
When judged result is without logic error, then to send Self-learning control and instruct to background monitoring module, background monitoring module connects
Receive after Self-learning control instruction, backstage technical staff is judged after the corresponding user instruction of input, self study by analogue simulation
Whether control instruction can make correct behavior reaction with control machine people:
If the behavior reaction made is correct, judges that Self-learning control instruction is correct, Self-learning control instruction is stored to machine
In the database of device people's control store instruction;
If the behavior reaction made is incorrect, Self-learning control instruction errors are judged, backstage technical staff is to self study control
Instruction processed is modified, and revised control instruction is stored into the database of control store instruction.
The beneficial effect of base case is:
Whether selftest module can have logic error with the instruction of effective detection Self-learning control, so as to be supervised to endowment robot
Pipe, provides more optimization, rational help for old man, also mitigates the workload of backstage technical staff;
Background monitoring module effectively ensures Self-learning control to the self-study control instruction operation result functional verification without logic error
The correctness of instruction, enhancing the elderly and the interactive function of endowment robot.
Further, in addition at random module is inspected by random samples, random sampling observation module is for randomly selecting the instruction and obtain that user sends
Take the control instruction in the corresponding database of user instruction to send to background monitoring module to be verified, backstage technical staff passes through
Analogue simulation, judges after the user instruction that input is randomly selected, whether corresponding control instruction can be made just with control machine people
True behavior reaction:
If the behavior reaction made is correct, judge that control instruction is correct;
If the behavior reaction made is incorrect, control instruction mistake is judged, show that control instruction is tampered, backstage technology people
Member is modified to control instruction, and revised control instruction is stored into the database of control store instruction.
Beneficial effect:Because endowment robot accessed external network, there is a situation where that instruction is distorted in assault, by with
Machine sampling observation control instruction carries out whether background authentication instruction is tampered, so that ensure that the correctness of control quality is correct, enhancing
The elderly interacts with endowment robot.
Further, in addition to electricity monitoring module, electricity monitoring module is used for the electricity for monitoring the battery of endowment robot,
And information about power is fed back into background monitoring module.Beneficial effect:Background monitoring personnel can understand endowment robot electricity in real time
The electricity in pond, is in time robot charging, it is to avoid because the use for not supplying electricity to the elderly is made troubles when robot does not have electricity soon.
Further, the electricity monitoring module includes electricity quantity display module and loudspeaker, and the electricity quantity display module is real-time
The electricity of battery is shown, it is low that the loudspeaker is used for voice message electricity.Beneficial effect:Electricity quantity display module shows battery in real time
Electricity, can conveniently check remaining electricity, when not enough power supply, charging, and carries out voice message by loudspeaker in time
Electricity is low, can effectively remind the elderly's not enough power supply, it is necessary to charge, it is to avoid because the use for not supplying electricity to the elderly is made troubles.
Further, the electricity monitoring module also includes gsm module, and gsm module is used to information about power feeding back to nurse
The mobile phone terminal of personnel.Beneficial effect:Because some the elderlys can not quickly acquistion support parents robot application method, information about power lead to
Cross gsm module to send to the mobile phone of caregiver, can be charged in time to robot by information about power caregiver, it is to avoid because
Not supplying electricity to the use of the elderly makes troubles.
Further, in addition to positioner, positioner is used for the positioning of robot, and positional information is fed back into backstage
Monitoring module.Beneficial effect:Positioning by positioner to robot, it may be determined that the position of nurse the elderly, to old age
People carries out monitoring position, prevents the elderly to wander away, and can be to some programs " run and fly ", the endowment machine not controlled by route
People is positioned, and is easy to personnel to look for.
Brief description of the drawings
Fig. 1 is the schematic front view of present invention endowment robot supervisory systems embodiment.
Embodiment
Below by embodiment, the present invention is further detailed explanation:
Reference in Figure of description includes:Self learning system 1, selftest module 2, background monitoring module 3, inspect mould by random samples at random
Block 4, electricity monitoring module 5, electricity quantity display module 51, loudspeaker 52, gsm module 53, positioner 6.
Endowment robot is substantially as shown in Figure 1 with supervisory systems embodiment:
The base case that the present invention is provided is:Endowment robot supervisory systems, including self learning system 1, the self study system
System 1 is used to carry out self-teaching to off-limits instruction, in addition to:
Selftest module 2, selftest module 2 is used to emulate Self-learning control instruction to judge that Self-learning control refers to by analog simulator
Whether order has logic error:
When judged result to there is logic error, then logic error result is fed back into self learning system 1, self learning system 1 is again
Study modification Self-learning control instruction;
When judged result is without logic error, then to send Self-learning control and instruct to next module;
The analogue system that the hardware of selftest module 2 is made up of handler mould board and periphery I/O plates isa bus, I/O plates and place
Data exchange can be carried out by shared drive/optical fiber interface between reason device.In software aspects, using Mathworks companies
Stateflow carries out command simulation.
Selftest module 2 is all provided with network interface card with background monitoring module 3, and the transmission of Self-learning control instruction is carried out by network.
Background monitoring module 3, background monitoring module 3 is used for the Self-learning control instruction for receiving the transmission of selftest module 2, backstage
Technical staff judges after the corresponding user instruction of input whether Self-learning control instruction can be with control machine by analogue simulation
People makes correct behavior reaction:
If the behavior reaction made is correct, judges that Self-learning control instruction is correct, Self-learning control instruction is stored to machine
In the database of device people's control store instruction;
If the behavior reaction made is incorrect, Self-learning control instruction errors are judged, backstage technical staff is to self study control
Instruction processed is modified, and revised control instruction is stored into the database of control store instruction.
If the behavior reaction made is incorrect, Self-learning control instruction errors are judged, backstage technical staff is to learning by oneself
Practise control instruction to be modified, and revised control instruction is stored into the database of control store instruction.
The hardware of background monitoring module 3 includes central processing unit, and central processing unit is using the stronger MIPS processing of compatibility
Device, is imitated the control instruction made referrals in software aspects using the Simbad robot simulations platform based on Java3D technologies
True simulation.
Also include sampling observation module 4 at random, random sampling observation module 4 is used to randomly select instruction and the acquisition user that user sends
Instruct the control instruction in corresponding database to send to background monitoring module 3 to be verified, backstage technical staff passes through emulation
Simulation, judges after the user instruction that input is randomly selected, whether corresponding control instruction can be made correctly with control machine people
Behavior reaction:
If the behavior reaction made is correct, judge that control instruction is correct;
If the behavior reaction made is incorrect, control instruction mistake is judged, show that control instruction is tampered, backstage technology people
Member is modified to control instruction, and revised control instruction is stored into the database of control store instruction.
Random sampling observation module 4 includes processor, and processor uses domestic Godson CPU, and control is referred to based on systematic sampling
Order is sampled checking, because endowment robot has accessed external network, there is the risk that instruction is distorted in assault, by random
Sampling observation control instruction carries out whether background authentication instruction is tampered, so as to ensure that the correctness of control quality is correct, enhances
The elderly interacts with endowment robot.
System also includes electricity monitoring module 5, and electricity monitoring module 5 is used for the electricity for monitoring the battery of endowment robot,
And information about power is fed back into background monitoring module 3, electricity monitoring module 5 includes electricity quantity display module 51 and loudspeaker 52, institute
The electricity that electricity quantity display module 51 shows battery in real time is stated, it is low that loudspeaker 52 is used for voice message electricity.Electricity monitoring module 5 is also
Including gsm module, gsm module is used for the mobile phone terminal that information about power is fed back to caregiver.
Because some the elderlys quickly can not support parents the application method of robot in acquistion, information about power sent by gsm module
To the mobile phone of caregiver, by information about power, caregiver can charge to robot in time, it is to avoid because not supplying electricity to the elderly
Use make troubles.Received for some new things than faster old man, the electricity shown in real time by electricity quantity display module 51
Pond electricity, can conveniently check remaining electricity, when not enough power supply, in time charging, and carries out voice by loudspeaker 52 and carry
Show that electricity is low, such as:" electricity is low, please charges in time ", can effectively remind the elderly's not enough power supply, it is necessary to charge.Background monitoring people
Member can understand the electricity of endowment robot battery in real time, when robot does not have electricity soon, be in time robot charging.
Wherein electricity monitoring module 5 carries Godson CPU and carries out data electricity monitoring, and electricity monitoring module 5 is surveyed including electricity
Circuit is measured, real time electrical quantity information is obtained by the voltage for monitoring battery.
Also include positioner 6, positioner 6 is used for the positioning of robot, and positional information is fed back into background monitoring
Module 3, wherein locating module are positioned using GPS, the positioning by positioner 6 to robot, it may be determined that nurse is old
The position of year people, carries out monitoring position to the elderly, prevents the elderly to wander away, and can to some programs " run and fly ", not by
The endowment robot of route control is positioned, and is easy to personnel to look for.
In use, self learning system 1 is carried out after self-teaching to off-limits instruction, the control that self study is completed is referred to
Order is sent to selftest module 2, and selftest module 2 emulates Self-learning control instruction to judge that Self-learning control refers to by analog simulator
Whether order has logic error:
When judged result to there is logic error, then logic error result is fed back into self learning system 1, self learning system 1 is again
Study modification Self-learning control instruction;
When judged result is without logic error, then to send Self-learning control and instruct to background monitoring module 3, background monitoring module 3
Receive after Self-learning control instruction, backstage technical staff is judged after the corresponding user instruction of input, learnt by oneself by analogue simulation
Practise whether control instruction can make correct behavior reaction with control machine people:
If the behavior reaction made is correct, judges that Self-learning control instruction is correct, Self-learning control instruction is stored to machine
In the database of device people's control store instruction;
Whether the present embodiment selftest module 2 can have logic error with the instruction of effective detection Self-learning control, also mitigate backstage skill
The workload of art personnel;Self-study control instruction operation result functional verification of 3 pairs of the background monitoring module without logic error, effectively really
Protect the correctness of Self-learning control instruction, enhancing the elderly and the interactive function of endowment robot.
Above-described is only that the known general knowledge such as concrete structure and characteristic is not made herein in embodiments of the invention, scheme
Excessive description, technical field that the present invention belongs to is all before one skilled in the art know the applying date or priority date
Ordinary technical knowledge, can know prior arts all in the field, and with using normal experiment hand before the date
The ability of section, one skilled in the art can improve and implement under the enlightenment that the application is provided with reference to self-ability
This programme, some typical known features or known method should not implement the application as one skilled in the art
Obstacle.It should be pointed out that for those skilled in the art, without departing from the structure of the invention, can also make
Go out several modifications and improvements, these should also be considered as protection scope of the present invention, these effects implemented all without the influence present invention
Fruit and practical applicability.The scope of protection required by this application should be based on the content of the claims, the tool in specification
Body embodiment etc. records the content that can be used for explaining claim.
Claims (6)
1. robot supervisory systems of supporting parents, including self learning system, the self learning system are used for off-limits instruction
Carry out self-teaching, it is characterised in that also include:
Selftest module, selftest module is used to emulate Self-learning control instruction to judge that Self-learning control is instructed by analog simulator
Whether logic error is had:
When judged result to there is logic error, then logic error result is fed back into self learning system, self learning system is learned again
Practise modification Self-learning control instruction;
When judged result is without logic error, then to send Self-learning control and instruct to next module;
Background monitoring module, background monitoring module is used for the Self-learning control instruction for receiving selftest module transmission, backstage technology people
Member judges after the corresponding user instruction of input whether Self-learning control instruction can be made with control machine people by analogue simulation
Correct behavior reaction:
If the behavior reaction made is correct, judges that Self-learning control instruction is correct, Self-learning control instruction is stored to machine
In the database of device people's control store instruction;
If the behavior reaction made is incorrect, Self-learning control instruction errors are judged, backstage technical staff is to self study control
Instruction processed is modified, and revised control instruction is stored into the database of control store instruction.
2. endowment robot according to claim 1 supervisory systems, it is characterised in that:Also include random sampling observation module,
Random sampling observation module is for randomly selecting the control instruction in the instruction and the corresponding database of acquisition user instruction that user sends
Send to background monitoring module and verified, backstage technical staff judges that the user that input is randomly selected refers to by analogue simulation
After order, whether corresponding control instruction can make correct behavior reaction with control machine people:
If the behavior reaction made is correct, judge that control instruction is correct;
If the behavior reaction made is incorrect, control instruction mistake is judged, show that control instruction is tampered, backstage technology people
Member is modified to control instruction, and revised control instruction is stored into the database of control store instruction.
3. endowment robot according to claim 2 supervisory systems, it is characterised in that:Also include electricity monitoring module,
Electricity monitoring module is used for the electricity for monitoring the battery of endowment robot, and information about power is fed back into background monitoring module.
4. endowment robot according to claim 3 supervisory systems, it is characterised in that:The electricity monitoring module includes
Electricity quantity display module and loudspeaker, the electricity quantity display module show the electricity of battery in real time, and the loudspeaker is carried for voice
Show that electricity is low.
5. endowment robot according to claim 4 supervisory systems, it is characterised in that:The electricity monitoring module is also wrapped
Gsm module is included, gsm module is used for the mobile phone terminal that information about power is fed back to caregiver.
6. according to any described endowment robot supervisory systems of claim 1-5, it is characterised in that:Also include positioning dress
Put, positioner is used for the positioning of robot, and positional information is fed back into background monitoring module.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201710508312.7A CN107255969B (en) | 2017-06-28 | 2017-06-28 | Endowment robot supervisory systems |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201710508312.7A CN107255969B (en) | 2017-06-28 | 2017-06-28 | Endowment robot supervisory systems |
Publications (2)
Publication Number | Publication Date |
---|---|
CN107255969A true CN107255969A (en) | 2017-10-17 |
CN107255969B CN107255969B (en) | 2019-10-18 |
Family
ID=60023503
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201710508312.7A Active CN107255969B (en) | 2017-06-28 | 2017-06-28 | Endowment robot supervisory systems |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN107255969B (en) |
Citations (15)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2005100421A (en) * | 2004-10-01 | 2005-04-14 | Fujitsu Ltd | Learning type self-localization device |
CN1676286A (en) * | 2004-04-02 | 2005-10-05 | 李朝辉 | Biological information follow-up instant-teaching control robot |
WO2008136737A1 (en) * | 2007-05-08 | 2008-11-13 | Institute Of Robotics In Scandinavia Ab | Self learning robot |
CN101782976A (en) * | 2010-01-15 | 2010-07-21 | 南京邮电大学 | Automatic selection method for machine learning in cloud computing environment |
CN103203753A (en) * | 2012-01-12 | 2013-07-17 | 三星电子株式会社 | Robot and method to recognize and handle exceptional situations |
CN103574004A (en) * | 2012-08-01 | 2014-02-12 | 上海通用汽车有限公司 | Self-learning adaptive control method and system for AMT system gear recognition references |
CN104317297A (en) * | 2014-10-30 | 2015-01-28 | 沈阳化工大学 | Robot obstacle avoidance method under unknown environment |
CN104965996A (en) * | 2015-07-23 | 2015-10-07 | 济南工程职业技术学院 | Elder life state monitoring and inference method based on Bayes formula |
CN105936047A (en) * | 2016-07-06 | 2016-09-14 | 厦门快商通科技股份有限公司 | Brain imitation robot controlling and studying system |
CN105991401A (en) * | 2015-02-05 | 2016-10-05 | 天脉聚源(北京)科技有限公司 | Network question-and-answer method and system |
CN106055718A (en) * | 2016-07-15 | 2016-10-26 | 北京光年无限科技有限公司 | Output content filtering method aiming at autonomic learning of robot and robot |
CN106393102A (en) * | 2015-07-31 | 2017-02-15 | 发那科株式会社 | Machine learning device, robot system, and machine learning method |
CN106454108A (en) * | 2016-11-04 | 2017-02-22 | 北京百度网讯科技有限公司 | Tracking shooting method and apparatus based on artificial intelligence, and electronic device |
CN106708950A (en) * | 2016-11-25 | 2017-05-24 | 北京光年无限科技有限公司 | Data processing method and device used for intelligent robot self-learning system |
CN106845628A (en) * | 2017-02-07 | 2017-06-13 | 珠海金萝卜智动科技有限公司 | The method and apparatus that robot generates new command by internet autonomous learning |
-
2017
- 2017-06-28 CN CN201710508312.7A patent/CN107255969B/en active Active
Patent Citations (15)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN1676286A (en) * | 2004-04-02 | 2005-10-05 | 李朝辉 | Biological information follow-up instant-teaching control robot |
JP2005100421A (en) * | 2004-10-01 | 2005-04-14 | Fujitsu Ltd | Learning type self-localization device |
WO2008136737A1 (en) * | 2007-05-08 | 2008-11-13 | Institute Of Robotics In Scandinavia Ab | Self learning robot |
CN101782976A (en) * | 2010-01-15 | 2010-07-21 | 南京邮电大学 | Automatic selection method for machine learning in cloud computing environment |
CN103203753A (en) * | 2012-01-12 | 2013-07-17 | 三星电子株式会社 | Robot and method to recognize and handle exceptional situations |
CN103574004A (en) * | 2012-08-01 | 2014-02-12 | 上海通用汽车有限公司 | Self-learning adaptive control method and system for AMT system gear recognition references |
CN104317297A (en) * | 2014-10-30 | 2015-01-28 | 沈阳化工大学 | Robot obstacle avoidance method under unknown environment |
CN105991401A (en) * | 2015-02-05 | 2016-10-05 | 天脉聚源(北京)科技有限公司 | Network question-and-answer method and system |
CN104965996A (en) * | 2015-07-23 | 2015-10-07 | 济南工程职业技术学院 | Elder life state monitoring and inference method based on Bayes formula |
CN106393102A (en) * | 2015-07-31 | 2017-02-15 | 发那科株式会社 | Machine learning device, robot system, and machine learning method |
CN105936047A (en) * | 2016-07-06 | 2016-09-14 | 厦门快商通科技股份有限公司 | Brain imitation robot controlling and studying system |
CN106055718A (en) * | 2016-07-15 | 2016-10-26 | 北京光年无限科技有限公司 | Output content filtering method aiming at autonomic learning of robot and robot |
CN106454108A (en) * | 2016-11-04 | 2017-02-22 | 北京百度网讯科技有限公司 | Tracking shooting method and apparatus based on artificial intelligence, and electronic device |
CN106708950A (en) * | 2016-11-25 | 2017-05-24 | 北京光年无限科技有限公司 | Data processing method and device used for intelligent robot self-learning system |
CN106845628A (en) * | 2017-02-07 | 2017-06-13 | 珠海金萝卜智动科技有限公司 | The method and apparatus that robot generates new command by internet autonomous learning |
Also Published As
Publication number | Publication date |
---|---|
CN107255969B (en) | 2019-10-18 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN105005658B (en) | Transformer station's integrated system apparatus logic emulation mode | |
CN101086760A (en) | Selective functional group simulation of automation control and information systems | |
CN104809663A (en) | Power professional technique service assurance surveillance system and method | |
CN109472550A (en) | The anti-human-equation error method, apparatus in million kilowatt nuclear power station and terminal device | |
CN110611312B (en) | On-line simulation system and method for panoramic data of substation bay level | |
CN110290223A (en) | Active upgrade method and system | |
CN110377136A (en) | A kind of PSU original value log recording method and device | |
CN109213658A (en) | A kind of method for inspecting and device | |
CN112216167A (en) | Booster station simulation operation automatic scoring system, method and equipment | |
CN103426041A (en) | Radiation source real-time monitoring and managing system and method based on Internet of things | |
CN203894630U (en) | Simulation debugging device of electric vehicle battery management system | |
CN111203869B (en) | Robot system maintenance method and device, robot and readable storage medium | |
CN103501256A (en) | Method for testing interchangeability of local communication unit of electric energy meter | |
CN107255969A (en) | Endowment robot supervisory systems | |
CN115471215B (en) | Business process processing method and device | |
CN103218928A (en) | Plant operation apparatus and plant operation training simulator apparatus | |
Elks et al. | Application of a fault injection based dependability assessment process to a commercial safety critical nuclear reactor protection system | |
CN109446642A (en) | A kind of grid equipment starting scheme intelligence write method and device | |
CN115827179A (en) | Computing power scheduling method, device, equipment and storage medium for physical machine equipment | |
CN107886180A (en) | Boat department creates single interface monitoring method, apparatus, electronic equipment, storage medium | |
Fernandez et al. | Open laboratory for robotics education | |
Han et al. | Power industry computer control system design and implementation problems: a case study of Poland | |
CN107038286B (en) | Power grid simulation method and device | |
CN107015815B (en) | Device for simulating safety control display equipment of nuclear power station | |
CN101635100A (en) | Portable computer test taking system and operation method thereof |
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 |