CN109539457A - A kind of cold water computer room control method based on deep learning - Google Patents
A kind of cold water computer room control method based on deep learning Download PDFInfo
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- CN109539457A CN109539457A CN201811267305.3A CN201811267305A CN109539457A CN 109539457 A CN109539457 A CN 109539457A CN 201811267305 A CN201811267305 A CN 201811267305A CN 109539457 A CN109539457 A CN 109539457A
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/30—Control or safety arrangements for purposes related to the operation of the system, e.g. for safety or monitoring
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/50—Control or safety arrangements characterised by user interfaces or communication
- F24F11/52—Indication arrangements, e.g. displays
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/50—Control or safety arrangements characterised by user interfaces or communication
- F24F11/56—Remote control
- F24F11/58—Remote control using Internet communication
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/62—Control or safety arrangements characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
- F24F11/63—Electronic processing
- F24F11/64—Electronic processing using pre-stored data
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/62—Control or safety arrangements characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
- F24F11/63—Electronic processing
- F24F11/65—Electronic processing for selecting an operating mode
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- Engineering & Computer Science (AREA)
- Chemical & Material Sciences (AREA)
- Combustion & Propulsion (AREA)
- Mechanical Engineering (AREA)
- General Engineering & Computer Science (AREA)
- Signal Processing (AREA)
- Physics & Mathematics (AREA)
- Fuzzy Systems (AREA)
- Mathematical Physics (AREA)
- Human Computer Interaction (AREA)
- Testing And Monitoring For Control Systems (AREA)
Abstract
The cold water computer room control method based on deep learning that the invention discloses a kind of, it is characterised in that: step 1, Local Controller obtains the computer room data that computer room issues；Step 2, Local Controller sends computer room data to machine learning controller；Step 3, machine learning controller sends computer room data to Cloud Server, and the control instruction controlled for the equipment to computer room is calculated by deep learning model in machine learning controller, wherein, Cloud Server passes through the processing to big data, deep learning model in Cloud Server is trained, and the deep learning model after training is sent to machine learning controller and is replaced.Than the control system for being currently based on PID or energy consumption model, cold water computer room control method of the present invention is based on machine learning, by to big data analysis, and the algorithm of deep learning finds more energy-efficient measures, new method is brought, to cold water machine room energy-saving so as to adapt to more complicated control scene.
Description
Technical field
The cold water computer room control method based on deep learning that the present invention relates to a kind of.
Background technique
Current machine learning method achieves quick development, is widely applied in fields such as image, speech recognitions.In cold water
In computer room, control system needs temperature collection, flow, pressure, equipment state, frequency converter frequency, fault alarm etc. hundreds and thousands of
A data point.Current cold water computer room control system generallys use pid algorithm and is controlled, and pid algorithm is just for required for it
Control object choose thousands of a data points certain it is several controlled, this algorithm only considered the efficiency of control target most
It is excellent, without considering influence of the operating status of the control object to entire cold water computer room operational energy efficiency.
Control system is controlled using water cooler energy consumption model, its shortcoming is that the control system only considers in model
Determining input data point, and the data point that model does not account for can not be reacted.Equipment in cold water computer room is all mutual
Associated, the variation of some temperature or flow can bring apparent variation to the operation of chilled water system.Using energy consumption model
Control system fortuitous event can not be reacted, and self-teaching can not be carried out, find other data points to energy consumption mould
The influence of type.
Summary of the invention
It is an object of the invention to overcome the above deficiencies in the existing technologies, and provide one kind be adapted to it is more multiple
The cold water computer room control method based on deep learning of miscellaneous control scene.
Technical solution used by the present invention solves the above problems is:
A kind of cold water computer room control method based on deep learning, it is characterised in that:
Step 1, Local Controller obtains the computer room data that computer room issues；
Step 2, Local Controller sends computer room data to machine learning controller；
Step 3, machine learning controller sends computer room data to Cloud Server, and machine learning controller passes through depth
The control instruction controlled for the equipment to computer room is calculated in learning model,
Wherein, Cloud Server is trained the deep learning model in Cloud Server by the processing to big data, and
Deep learning model after training is sent to machine learning controller to be replaced.
Than the control system for being currently based on PID or energy consumption model, cold water computer room control method of the present invention is based on engineering
It practises, more energy-efficient measures is found by the algorithm to big data analysis and deep learning, cold water machine room energy-saving is brought newly
Method, so as to adapt to more complicated control scene.
Further, preferably, the Local Controller monitors the operating status of each calculator room equipment in real time, if a certain
Calculator room equipment breaks down, and will alarm immediately.
Further, preferably, Local Controller built-in security boundary monitoring system, when the fortune of cold water room system
Row is more than the security boundary of setting, and pressure is switched to security operating mode, the parameter operation being automatically adjusted in security boundary.
Further, preferably, the control program of the Local Controller is according to circumstances in pid control algorithm, depth
It practises and being switched between algorithm and manual operation control model, manual operation control model highest priority, followed by depth
Practise algorithm and pid control algorithm.
Further, preferably, basic cold water computer room PID control logic, cold water built in the control system of Local Controller
Opening of device/closing sequential control logic and safety protection control logic in computer room.
Further, preferably, the Local Controller is equipped with the dual pressure manual command interface of software and hardware, when
After manual command's interface to the order for forcing manual command, it is excellent that the control system of Local Controller immediately enters manual control
First mode, all automatic control algorithms are out of service.
Further, preferably, the computer room data include calculator room equipment data and environmental sensor data.
Further, preferably, in step 2, the computer room data that Local Controller is first read are removed abnormal Value Operations
Afterwards, by real-time data transmission to machine learning controller.
Further, preferably, the machine learning controller is when encountering failure, machine learning controller is first attempted certainly
Dynamic error correction or the control system for restarting machine learning controller.
Further, preferably, the Cloud Server passes through network connection to the remote terminal for being used to access data.Remotely
Terminal gets the real-time information of cold water computer room, is remotely supervised to the operation conditions of cold water computer room and entire control system
Control.
Further, preferably, computer room data are successively transmitted to Local Controller, machine learning controller, Cloud Server
In the process, computer room data by Local Controller, machine learning controller, the respective secure verification module of Cloud Server carry out into
The analysis of row data, if the computer room data read are more than preset safety regulation display alarm information immediately,
Specifically:
In step 1, Local Controller carries out data analysis using third layer secure verification module to data, if the number read
According to being more than preset safety regulation display alarm information immediately, and warning message is uploaded into machine learning controller.
In step 2, after machine learning controller receives the data of Local Controller, second layer secure verification module is used
To data screening, if received data are more than safety regulation display alarm information immediately, and warning message is transferred to and is controlled on the spot
Device and Cloud Server processed, if received data transfer data to Cloud Server in safety regulation.
In step 3, after Cloud Server receives the data of machine learning controller, first layer secure verification module pair is used
Data screening if received data are more than safety regulation display alarm information immediately, and warning message is transferred to regard to engineering
Practise controller.
Further, preferably, control instruction in step 3 is via Cloud Server, learning controller and on the spot controls
Device carries out safety verification, and after safety verification passes through, calculator room equipment executes control instruction.
Further, preferably, Cloud Server, machine learning controller and Local Controller are respectively provided with independent peace
Full authentication mechanism.After control instruction only has while meeting multi-level safety authentication mechanism, after safety verification passes through, control instruction is sent
It is executed to each equipment in cold water computer room, and that the control instruction is sent to Cloud Server simultaneously is standby for deep learning controller
Part.
Compared with prior art, the present invention having the following advantages that and effect: the control than being currently based on PID or energy consumption model
System processed, cold water computer room control method of the present invention are based on machine learning, pass through the algorithm to big data analysis and deep learning
More energy-efficient measures are found, bring new method, to cold water machine room energy-saving so as to adapt to more complicated control scene.
Detailed description of the invention
Fig. 1 is the hardware block diagram of cold water computer room control system of the embodiment of the present invention.
Fig. 2 is that the software function module of cold water computer room control system of the embodiment of the present invention constitutes schematic diagram.
Fig. 3 is the part control flow schematic diagram of cold water computer room control system of the embodiment of the present invention.
Specific embodiment
The present invention is described in further detail with reference to the accompanying drawing and by embodiment, and following embodiment is to this hair
Bright explanation and the invention is not limited to following embodiments.
Referring to Fig. 1, the present embodiment cold water computer room control system includes calculator room equipment, sensor data acquisition module, on the spot
Controller, machine learning controller, Cloud Server and remote terminal, calculator room equipment, sensor data acquisition module are connected to
Local Controller.Local Controller, machine learning controller and Cloud Server, remote terminal are sequentially connected, and connection type can
Using the conventional communications connection type such as connection, cable, wireless.
By taking water-cooled cold water computer room as an example, calculator room equipment includes cold water main unit, water pump, cooling tower, frequency converter.Sensor number
It include temperature sensor, humidity sensor, flow sensor, pressure sensor, air flow sensor according to acquisition module.Computer room is set
Standby, sensor data acquisition module is connected to Local Controller by I/O interface.Local Controller uses PLC, DDC or industry control
Machine.
Basic cold water computer room PID control logic built in the control system of Local Controller, opening of device/pass in cold water computer room
Sequential control logic, safety protection control logic and the security boundary monitoring system closed, the Local Controller is equipped with soft
Part and the dual pressure manual command interface of hardware.
Remote terminal can use mobile phone, computer, plate and other intelligent terminal.
Referring to fig. 2, the function of each component part of cold water computer room control system is as described below:
A. sensor data acquisition module (abbreviation sensor module), function is: obtaining temperature, humidity, flow, pressure
The parameter informations such as power, air quantity, and it is sent to Local Controller
B. Local Controller, function include: (1) by I/O input/output module be monitored and controlled cold water main unit, water pump,
Cooling tower, frequency converter and sensor data acquisition module；(2) with machine learning controller communication, controller is interior to be protected comprising equipment
Authentication mechanism is protected, after receiving the control instruction of machine learning controller, according to protection authentication mechanism and rule, is ensuring
Judge whether to execute the instruction in the case where system safe operation.(3) it can force to switch to manual command's mode.
C. machine learning controller, function include: that (1) is screened, arranged and deposited to from Local Controller reading data
Storage.(2) use calculates best cold water computer room control instruction, and should through the trained deep learning model of machine learning in real time
Control instruction is sent to Local Controller.(3) receive and send data to Cloud Server.(4) there is automatic error-correcting and automatic weight
Open function.It (5) include secure authentication mechanisms and equipment run-limiting condition.Guarantee equipment operating instruction in safe operation model
In enclosing.
D. Cloud Server, function include: the data that (1) receives the transmission of machine learning controller, carry out classification storage.(2)
Big data analysis and machine learning are carried out to the data of collection, continuous iteration updates cold water computer room deep learning model.(3) every
In a cycle, using the control system of the machine learning model optimization cold water computer room after iteration, and sends and give machine learning control
Device processed.The equal build-in depths learning model of the control program of machine learning controller and Cloud Server, (4) include safety verification machine
System and equipment run-limiting condition.Guarantee equipment operating instruction in operational envelope.
E. the function of remote terminal is: Cloud Server is connected to, so that the real-time information of cold water computer room is got, to cold
The operation conditions of water dispenser room and entire control system is remotely monitored.
Referring to Fig. 3, the control process of cold water computer room control system includes the following steps,
(1) step 1, Local Controller obtain the computer room data that computer room issues；
(2) step 2, Local Controller send computer room data to machine learning controller；
(3) step 3, machine learning controller transmission computer room data to Cloud Server, and machine learning controller passes through
The control instruction controlled for the equipment to computer room is calculated in deep learning model,
(4) step 4, control instruction carry out safety verification, peace via Cloud Server, learning controller and Local Controller
After full verifying passes through, calculator room equipment executes control instruction.Cloud Server, machine learning controller and Local Controller are set respectively
First layer secure verification module, second layer secure verification module, third layer secure verification module are set.Control instruction is only simultaneously
After the secure authentication mechanisms for meeting multi-level safety authentication module, after safety verification passes through, control instruction is sent in cold water computer room
Each equipment execute, and deep learning controller simultaneously by the control instruction be sent to Cloud Server backup.
In above-mentioned steps 3, after machine learning controller sends computer room data to Cloud Server, Cloud Server passes through to big number
According to processing, the deep learning model in Cloud Server is trained, and periodically by after training deep learning model send
It is replaced to machine learning controller.Than the control system for being currently based on PID or energy consumption model, cold water computer room control of the present invention
Method processed is based on machine learning, more energy-efficient measures is found by the algorithm to big data analysis and deep learning, to cold
Water machine room energy-saving brings new method, so as to adapt to more complicated control scene.
In the control process of cold water computer room control system, computer room data are successively transmitted to Local Controller, machine learning control
During device processed, Cloud Server, computer room data pass through Local Controller, machine learning controller, the respective safety of Cloud Server
Authentication module carries out carrying out data analysis, if the computer room data read are more than that preset safety regulation shows alarm signal immediately
Breath.
Specifically:
In step 1, Local Controller carries out data analysis using third layer secure verification module to data, if the number read
According to being more than preset safety regulation display alarm information immediately, and warning message is uploaded into machine learning controller.
In step 2, after machine learning controller receives the data of Local Controller, second layer secure verification module is used
To data screening, if received data are more than safety regulation display alarm information immediately, and warning message is transferred to and is controlled on the spot
Device and Cloud Server processed, if received data transfer data to Cloud Server in safety regulation.
In step 3, after Cloud Server receives the data of machine learning controller, first layer secure verification module pair is used
Data screening if received data are more than safety regulation display alarm information immediately, and warning message is transferred to regard to engineering
Practise controller.
In the cold water computer room control system course of work, the progress of Local Controller works as follows
(1) Local Controller monitors the operating status of each calculator room equipment in real time, if a certain calculator room equipment breaks down,
It will alarm immediately.
(2) when the security boundary for running more than setting of cold water room system, pressure is switched to security operating mode.
(3) the control program of the Local Controller is according to circumstances in pid control algorithm, deep learning algorithm and artificial behaviour
Make to switch between control model.
(4) when manual command's interface is to after the order for forcing manual command, [Local Controller] control system is vertical
Enter manual control mode of priority, all automatic control algorithms are out of service.
(5) after the computer room data that Local Controller is first read are removed abnormal Value Operations, data are real-time in step 2
It is transferred to machine learning controller.
For the machine learning controller when encountering uncertain failure, machine learning controller first attempts automatic error-correcting
Or restart；
In industrial control field, especially cold water computer room control system, the reliability of control system and safety are most
Important aspect.Deep learning itself lacks robustness, and to the new situation not learnt, it is difficult to predict the characteristics such as behavior.Therefore
Deep learning is applied in cold water computer room control system, lacking for the control system robust based on deep learning algorithm how is overcome
Point, Guarantee control system safe operation is an important problem.
Deep learning algorithm is applied in cold water computer room control system, system is needed to be optimized, to overcome machine
Learn the robustness problem of itself.Method of the present invention use following security mechanism improve control system robustness and
Safety:
1. multi-tier authentication: Cloud Server, machine learning controller and Local Controller are respectively provided with independent safety and test
Card mechanism.After control instruction only has while meeting multi-level safety authentication mechanism, can just it execute；
2. real time monitoring: Local Controller can monitor the operating status of each equipment in real time, if a certain equipment occurs
Failure will alarm immediately；
3. automatic error-correcting and restarting: machine learning controller contains automatic error-correcting and restarts function, can not be pre- when encountering
When the failure of survey, which first attempts automatic error-correcting or restarts；
4. control algolithm free switching: Local Controller can be in pid control algorithm, deep learning algorithm and manual operation
Etc. switch between control models；
5. security boundary monitoring system: Local Controller executes equipment, built-in security boundary as last control instruction
Monitoring system.When the security boundary for running more than setting of cold water room system, pressure is switched to security operating mode；
6. forcing manual control: being equipped with the dual pressure manual command interface of software and hardware.It is forced manually when receiving
After the order of instruction, control system immediately enters manual control mode of priority, and all automatic control algorithms are out of service.
Above content is only illustrations made for the present invention described in this specification.Technology belonging to the present invention
The technical staff in field can make various modifications or additions to the described embodiments or by a similar method
Substitution, content without departing from description of the invention or beyond the scope defined by this claim should belong to this
The protection scope of invention.
Claims (10)
1. a kind of cold water computer room control method based on deep learning, it is characterised in that:
Step 1, Local Controller obtains the computer room data that computer room issues；
Step 2, Local Controller sends computer room data to machine learning controller；
Step 3, machine learning controller sends computer room data to Cloud Server, and machine learning controller passes through deep learning
The control instruction controlled for the equipment to computer room is calculated in model,
Wherein, Cloud Server is trained the deep learning model in Cloud Server by the processing to big data, and will instruction
Deep learning model after white silk is sent to machine learning controller and is replaced.
2. the cold water computer room control method according to claim 1 based on deep learning, it is characterised in that: described to control on the spot
Device processed monitors the operating status of each calculator room equipment in real time, if a certain calculator room equipment breaks down, will alarm immediately.
3. the cold water computer room control method according to claim 1 based on deep learning, it is characterised in that: described to control on the spot
Pressure is switched to by device built-in security processed boundary monitoring system when the security boundary for running more than setting of cold water room system
Security operating mode.
4. the cold water computer room control method according to claim 1 based on deep learning, it is characterised in that: described to control on the spot
The control program of device processed is according to circumstances cut between pid control algorithm, deep learning algorithm and manual operation control model
It changes.
5. the cold water computer room control method according to claim 1 based on deep learning, it is characterised in that: Local Controller
Control system built in basic cold water computer room PID control logic, in cold water computer room opening of device/closing sequential control logic with
And safety protection control logic.
6. the cold water computer room control method according to claim 1 based on deep learning, it is characterised in that: described to control on the spot
Device processed is equipped with the dual pressure manual command interface of software and hardware, when manual command's interface to the life for forcing manual command
After order, the control system of Local Controller immediately enters manual control mode of priority, and all automatic control algorithms are out of service.
7. the cold water computer room control method according to claim 1 based on deep learning, it is characterised in that: in step 2, just
After the computer room data that ground controller is first read are removed abnormal Value Operations, by real-time data transmission to machine learning controller.
8. the cold water computer room control method according to claim 1 based on deep learning, it is characterised in that: the engineering
Controller is practised when encountering uncertain failure, machine learning controller is first attempted automatic error-correcting or restarted.
9. the cold water computer room control method according to claim 1 based on deep learning, it is characterised in that: computer room data according to
Secondary to be transmitted to during Local Controller, machine learning controller, Cloud Server, computer room data pass through Local Controller, machine
The respective secure verification module of learning controller, Cloud Server carries out carrying out data analysis, if the computer room data read are more than pre-
The safety regulation first set display alarm information immediately.
10. the cold water computer room control method according to claim 1 based on deep learning, it is characterised in that: in step 3
Control instruction carries out safety verification, after safety verification passes through, machine via Cloud Server, learning controller and Local Controller
Room equipment executes control instruction.
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| CN112628956A (en) * | 2020-12-24 | 2021-04-09 | 华中科技大学 | Water chilling unit load prediction control method and system based on edge cloud cooperative framework |
| CN114879542A (en) * | 2022-05-25 | 2022-08-09 | 罗杰韦尔控制系统(广州)股份有限公司 | Machine learning-based efficient cold water machine room control system and method |
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Application publication date: 20190329 |