CN108921223A - A kind of server cooling system and control method, computer program, computer - Google Patents
A kind of server cooling system and control method, computer program, computer Download PDFInfo
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- CN108921223A CN108921223A CN201810732051.1A CN201810732051A CN108921223A CN 108921223 A CN108921223 A CN 108921223A CN 201810732051 A CN201810732051 A CN 201810732051A CN 108921223 A CN108921223 A CN 108921223A
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Abstract
The invention belongs to server cooling technology field, a kind of server cooling system and control method, computer program, computer are disclosed, air volume test module detection service device air quantity of fan data are passed through；Central control module dispatches air cooling module and carries out cooling down operation by fan blowing；Cooling down operation is carried out using liquid by liquid cooled module；By the automatic detection service device hard disk secure state of automatic maintenance module and safeguarded；Judge whether exception according to temperature, the air quantity data of detection by alarm module, if abnormal and alarm.The present invention realizes the accurate monitoring to server air quantity according to the self-operating state output air quantity information of its power module (i.e. server power supply), and then convenient for the radiator of data center convenient for server by air volume test module；Simultaneously hard disk exception can be found by automatic maintenance module in time, can safeguarded in time, the advantages of maintenance cost is low and high reliablity.
Description
Technical field
The invention belongs to server cooling technology field more particularly to a kind of server cooling system and control methods, meter
Calculation machine program, computer.
Background technique
Currently, the prior art commonly used in the trade is such：
Server, also referred to as servomechanism are to provide the equipment of the service of calculating.Since server needs to respond service request, and
It is handled, therefore in general server should have the service of undertaking and ensure the ability of service.The composition of server includes
Processor, hard disk, memory, system bus etc. are similar with general computer architecture, but due to needing to provide highly reliable clothes
Business, thus processing capacity, stability, reliability, safety, scalability, in terms of it is more demanding.However,
Existing server cooling system cannot accurate detection service device air quantity of fan data in time, the unfavorable prison to server radiating
It surveys；If server hard disc is abnormal simultaneously, it cannot safeguard in time, lead to servers go down.
In conclusion problem of the existing technology is：
Existing server cooling system cannot accurate detection service device air quantity of fan data in time, it is unfavorable that server is dissipated
The monitoring of heat；If server hard disc is abnormal simultaneously, it cannot safeguard in time, lead to servers go down.
Deviation threat from temperature has the characteristics that its is exclusive, ambiguity, uncertainty and timeliness etc., therefore not
Temperature deviation can be quantitatively analyzed with conventional method, such as function method to threaten.It is such as engineered mathematical model Evaluation Method, they
There is significant limitation, because of the constraint of self-condition, propinquity effect and pessimistic that reasoning by analogy goes out.And lack to temperature
Deviation information timeliness analysis, cannot reflect temperature deviation threaten different moments changing rule.Cause not can be carried out
Temperature accurately controls.
Summary of the invention
In view of the problems of the existing technology, the present invention provides a kind of server cooling system and control methods.
The invention is realized in this way a kind of control method of server cooling system, the server cooling system
Control method includes：
Nonlinear transformation is carried out to received temperature signal s (t) by temperature detecting module, is carried out as follows：
WhereinA
Indicate the amplitude of signal, a (m) indicates that the symbol of signal, p (t) indicate shaping function, fcIndicate the carrier frequency of signal,Indicate the phase of signal, and by obtaining after the nonlinear transformationCarry out server work
Temperature data detection；
Detection service device air quantity of fan data are carried out using received air quantity of fan signal y (t) by air volume test module,
Y (t) is expressed as：
Y (t)=x (t)+n (t)；
Wherein, x (t) is digital modulation signals, and n (t) is the impulsive noise of obedience standard S α S distribution, the parsing shape of x (t)
Formula is expressed as：
Wherein, N is sampling number, anFor the information symbol of transmission, in MASK signal, an=0,1,2 ..., M-1, M are
Order of modulation, an=ej2πε/M, ε=0,1,2 ..., M-1, g (t) expression rectangle molding pulse, TbIndicate symbol period, fcIt indicates
Carrier frequency, carrier wave initial phaseIt is the equally distributed random number in [0,2 π]；
Central control module dispatches air cooling module and carries out cooling down operation by fan blowing；Liquid is used by liquid cooled module
Carry out cooling down operation；
Central control module is dispatched in air cooling module, by the server temperature information of collection, server fan air quantity information
Quantification treatment is carried out according to the quantification gradation of division, and establishes observation evidence table；
The conditional probability transfer matrix between state is established using expertise or experience, determines that the state between time slice turns
Move matrix；
It establishes temperature threat level and influences the discrete dynamic Bayesian network model of temperature factor；
Using observation evidence table, conditional transition probability table and the state transition probability table of foundation, pushed away with Hidden Markov
Adjustment method calculates final temperature threat level；Control instruction is issued, air cooling module is scheduled；
By the automatic detection service device hard disk secure state of automatic maintenance module and safeguarded；
Judge whether exception according to temperature, the air quantity data of detection by alarm module, if abnormal and alarm.
Further, the discrete dynamic Bayesian network model is the directed acyclic being made of observer nodes and state node
Figure, server temperature, server fan air quantity collectively form discrete state node, and temperature threat level is observer nodes.
Further, observation evidence table, conditional transition probability table and the state transition probability table of the foundation, in conjunction with being established
Discrete dynamic Bayesian network model, determine that final threat level is Bayesian inference processes according to a large amount of state nodes
Data reasoning goes out the probability of observer nodes maximum possible value；
It specifically includes：System parameter λ and observation sequence Y, Forward-backward algorithm infer the process of probability P (Y | λ) such as
Under：
Forwards algorithms define forward variable αt(i)=P (y1,y2,...,yt,xt=i | λ)
Initialization：α1(i)=πibi(y1), 1≤i≤n
Recursive operation：
As a result：
Backward algorithm, to variable β after definitiont(i)=P (yt+1,yt+2,...,yT|xt=i, λ)
Initialization：βT(i)=1,1≤i≤n
Recursive operation：
As a result：
Forwards algorithms, backward algorithm are combined into composition Forward-backward algorithm：
Finally, according to established observation evidence table, conditional transition probability table and state transition probability table, in conjunction with it is preceding to-after
The temperature threat level of UAV is inferred to algorithm；
The state set of each node is indicated with S in the discrete dynamic Bayesian network model, each factor subscript area
Point, as follows：
STT={ serious, normal }.
Further, air volume detecting method includes：
Firstly, being based respectively on the PWM value for the power supply fan that it currently gets；
Then, the power module ventilation quantity Q according to the Cabinet-type server pre-established is corresponding with power supply fan PWM value
Functional relation Q=f (PWM)；The current ventilation quantity Q of current server power block to be monitored is calculated, this can be exported later
Currently calculate resulting ventilation quantity Q.
Further, hard disk automatic maintenance method includes：
Firstly, the state of detection hard disk；
Then, judge whether the hard disk is abnormal, if the hard disk is abnormal, receives exception information and the place of the hard disk
The zone position information where the hard disk in abnormality is positioned and is identified to the hard disk in abnormality
The hard disk in abnormality；
Finally, controlling robot motion according to the exception information and the location information of the hard disk in abnormality
To the regional location of the hard disk in abnormality；The mark of the hard disk of the robot identification in abnormality
Know, to obtain the location information of the hard disk in abnormality, and by the hard disk taking-up in abnormality and more
It is changed to the hard disk of normal work.
Another object of the present invention is to provide a kind of computers of control method for realizing the server cooling system
Program.
Another object of the present invention is to a kind of information computers of control method for realizing the server cooling system.
Another object of the present invention is to a kind of computer readable storage mediums, including instruction, when it is transported on computers
When row, so that computer executes the control method of the server cooling system.
Another object of the present invention is to a kind of server cooling system for realizing the control method, server cooling systems
System includes：
Power module is connect with central control module, for being powered to server modules；
Temperature detecting module is connect with central control module, for passing through temperature sensor detection service device operating temperature
Data；
Air volume test module, connect with central control module, is used for detection service device air quantity of fan data；
Central control module, with power module, temperature detecting module, air volume test module, air cooling module, liquid cooled module,
Automatic maintenance module, alarm module connection, work normally for controlling modules；
Air cooling module is connect with central control module, carries out cooling down operation for drying by fan；
Liquid cooled module is connect with central control module, for carrying out cooling down operation by liquid；
Automatic maintenance module, connect with central control module, for automatic detection service device hard disk secure state and carries out
Maintenance；
Alarm module is connect with central control module, for judging whether exception according to temperature, the air quantity data of detection,
If abnormal and alarm.
Another object of the present invention is to a kind of servers for Industry Control for carrying the server cooling system.
Advantages of the present invention and good effect are：
The present invention is by air volume test module convenient for server according to itself fortune of its power module (i.e. server power supply)
Row state output air quantity information, and then the accurate monitoring to server air quantity is realized convenient for the radiator of data center；Lead to simultaneously
The advantages of hard disk exception can be found in time by crossing automatic maintenance module, can be safeguarded in time, and maintenance cost is low and high reliablity.
The present invention by temperature detecting module to received temperature signal s (t) carry out nonlinear transformation, as follows into
Row：
WhereinA
Indicate the amplitude of signal, a (m) indicates that the symbol of signal, p (t) indicate shaping function, fcIndicate the carrier frequency of signal,Indicate the phase of signal, and by obtaining after the nonlinear transformationCarry out server work
Temperature data detection；
Detection service device air quantity of fan data are carried out using received air quantity of fan signal y (t) by air volume test module,
Y (t) is expressed as：
Y (t)=x (t)+n (t)；
Wherein, x (t) is digital modulation signals, and n (t) is the impulsive noise of obedience standard S α S distribution, the parsing shape of x (t)
Formula is expressed as：
Wherein, N is sampling number, anFor the information symbol of transmission, in MASK signal, an=0,1,2 ..., M-1, M are
Order of modulation, an=ej2πε/M, ε=0,1,2 ..., M-1, g (t) expression rectangle molding pulse, TbIndicate symbol period, fcIt indicates
Carrier frequency, carrier wave initial phaseIt is the equally distributed random number in [0,2 π]；It can get accurate temperature and air quantity letter
Number, foundation is provided for the intelligent control of next step.
The present invention realizes the combination of continuous measurements and discrete dynamic Bayesian network, by all temperature deviation prestige
The relevant important factor of stress integrates carry out judging and deducing, establishes suitable for the discrete dynamic of temperature deviation Threat reasoning
State Bayesian network model (see Fig. 3), and combine the probability distribution for inferring threat degree；Assess temperature deviation effective
Property, practicability and accuracy greatly promote；Compared with static Bayesian Network, discrete dynamic Bayesian network faces due to being utilized
The nodal information of nearly period, therefore the reasoning results accuracy is higher, and when data are there are under exception or uncertain condition, it is discrete
Dynamic bayesian network still is able to infer more correct temperature deviation threat level.
Detailed description of the invention
Fig. 1 is the control method flow chart that the present invention implements the server cooling system provided.
Fig. 2 is that the present invention implements the server cooling system structure figure provided.
In figure：1, power module；2, temperature detecting module；3, air volume test module；4, central control module；5, air-cooled mould
Block；6, liquid cooled module；7, automatic maintenance module；8, alarm module.
Fig. 3 is that the present invention implements the discrete dynamic Bayesian network model suitable for the reasoning of temperature deviation Threat provided
Figure.
Specific embodiment
In order to make the objectives, technical solutions, and advantages of the present invention clearer, with reference to embodiments, to the present invention
It is further elaborated.It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, it is not used to
Limit the present invention.
With reference to the accompanying drawing and specific embodiment is further described application principle of the invention.
As shown in Figure 1, a kind of server cooling system provided by the invention and control method include the following steps：
S101 is powered by electric power source pair of module server modules；
S102 passes through temperature detecting module detection service device operating temperature data；Pass through air volume test module detection service
Device air quantity of fan data；
S103, central control module dispatch air cooling module and carry out cooling down operation by fan blowing；It is adopted by liquid cooled module
Cooling down operation is carried out with liquid；
S104 by the automatic detection service device hard disk secure state of automatic maintenance module and is safeguarded；
S105 judges whether exception according to temperature, the air quantity data of detection by alarm module, if abnormal and Times
It is alert.
As shown in Fig. 2, server cooling system provided in an embodiment of the present invention includes：Power module 1, temperature detecting module
2, air volume test module 3, central control module 4, air cooling module 5, liquid cooled module 6, automatic maintenance module 7, alarm module 8.
Power module 1 is connect with central control module 4, for being powered to server modules；
Temperature detecting module 2 is connect with central control module 4, for passing through temperature sensor detection service device work temperature
Degree evidence；
Air volume test module 3 is connect with central control module 4, is used for detection service device air quantity of fan data；
Central control module 4, with power module 1, temperature detecting module 2, air volume test module 3, air cooling module 5, liquid cooling
Module 6, automatic maintenance module 7, alarm module 8 connect, and work normally for controlling modules；
Air cooling module 5 is connect with central control module 4, carries out cooling down operation for drying by fan；
Liquid cooled module 6 is connect with central control module 4, for carrying out cooling down operation by liquid；
Automatic maintenance module 7, connect with central control module 4, goes forward side by side for automatic detection service device hard disk secure state
Row maintenance；
Alarm module 8 is connect with central control module 4, is judged whether for temperature, the air quantity data according to detection different
Often, if abnormal and alarm.
3 detection method of air volume test module provided in an embodiment of the present invention is as follows：
Firstly, being based respectively on the PWM value for the power supply fan that it currently gets；
Then, the power module ventilation quantity Q according to the Cabinet-type server pre-established is corresponding with power supply fan PWM value
Functional relation Q=f (PWM)；The current ventilation quantity Q of current server power block to be monitored is calculated, this can be exported later
Currently calculate resulting ventilation quantity Q.
7 maintaining method of automatic maintenance module provided by the invention is as follows：
Firstly, the state of detection hard disk；
Then, judge whether the hard disk is abnormal, if the hard disk is abnormal, receives exception information and the place of the hard disk
The zone position information where the hard disk in abnormality is positioned and is identified to the hard disk in abnormality
The hard disk in abnormality；
Finally, controlling robot motion according to the exception information and the location information of the hard disk in abnormality
To the regional location of the hard disk in abnormality；The mark of the hard disk of the robot identification in abnormality
Know, to obtain the location information of the hard disk in abnormality, and by the hard disk taking-up in abnormality and more
It is changed to the hard disk of normal work.
Below with reference to concrete analysis, the invention will be further described.
The control method of server cooling system provided in an embodiment of the present invention, the controlling party of the server cooling system
Method includes：
Nonlinear transformation is carried out to received temperature signal s (t) by temperature detecting module, is carried out as follows：
WhereinA
Indicate the amplitude of signal, a (m) indicates that the symbol of signal, p (t) indicate shaping function, fcIndicate the carrier frequency of signal,Indicate the phase of signal, and by obtaining after the nonlinear transformationCarry out server work
Temperature data detection；
Detection service device air quantity of fan data are carried out using received air quantity of fan signal y (t) by air volume test module,
Y (t) is expressed as：
Y (t)=x (t)+n (t)；
Wherein, x (t) is digital modulation signals, and n (t) is the impulsive noise of obedience standard S α S distribution, the parsing shape of x (t)
Formula is expressed as：
Wherein, N is sampling number, anFor the information symbol of transmission, in MASK signal, an=0,1,2 ..., M-1, M are
Order of modulation, an=ej2πε/M, ε=0,1,2 ..., M-1, g (t) expression rectangle molding pulse, TbIndicate symbol period, fcIt indicates
Carrier frequency, carrier wave initial phaseIt is the equally distributed random number in [0,2 π]；
Central control module dispatches air cooling module and carries out cooling down operation by fan blowing；Liquid is used by liquid cooled module
Carry out cooling down operation；
Central control module is dispatched in air cooling module, by the server temperature information of collection, server fan air quantity information
Quantification treatment is carried out according to the quantification gradation of division, and establishes observation evidence table；
The conditional probability transfer matrix between state is established using expertise or experience, determines that the state between time slice turns
Move matrix；
It establishes temperature threat level and influences the discrete dynamic Bayesian network model of temperature factor；
Using observation evidence table, conditional transition probability table and the state transition probability table of foundation, pushed away with Hidden Markov
Adjustment method calculates final temperature threat level；Control instruction is issued, air cooling module is scheduled；
By the automatic detection service device hard disk secure state of automatic maintenance module and safeguarded；
Judge whether exception according to temperature, the air quantity data of detection by alarm module, if abnormal and alarm.
The discrete dynamic Bayesian network model is the directed acyclic graph being made of observer nodes and state node, service
Device temperature, server fan air quantity collectively form discrete state node, and temperature threat level is observer nodes.
Observation evidence table, conditional transition probability table and the state transition probability table of the foundation, it is discrete in conjunction with what is established
Dynamic Bayesian network model determines that final threat level is that Bayesian inference processes are pushed away according to a large amount of state node data
Manage out the probability of observer nodes maximum possible value；
It specifically includes：System parameter λ and observation sequence Y, Forward-backward algorithm infer the process of probability P (Y | λ) such as
Under：
Forwards algorithms define forward variable αt(i)=P (y1,y2,...,yt,xt=i | λ)
Initialization：α1(i)=πibi(y1),1≤i≤n
Recursive operation：
As a result：
Backward algorithm, to variable β after definitiont(i)=P (yt+1,yt+2,...,yT|xt=i, λ)
Initialization：βT(i)=1,1≤i≤n
Recursive operation：
As a result：
Forwards algorithms, backward algorithm are combined into composition Forward-backward algorithm：
Finally, according to established observation evidence table, conditional transition probability table and state transition probability table, in conjunction with it is preceding to-after
The temperature threat level of UAV is inferred to algorithm；
The state set of each node is indicated with S in the discrete dynamic Bayesian network model, each factor subscript area
Point, as follows：
STT={ serious, normal }.
Fig. 3 is that the present invention implements the discrete dynamic Bayesian network model suitable for the reasoning of temperature deviation Threat provided
Figure.
In the above-described embodiments, can come wholly or partly by software, hardware, firmware or any combination thereof real
It is existing.When using entirely or partly realizing in the form of a computer program product, the computer program product include one or
Multiple computer instructions.When loading on computers or executing the computer program instructions, entirely or partly generate according to
Process described in the embodiment of the present invention or function.The computer can be general purpose computer, special purpose computer, computer network
Network or other programmable devices.The computer instruction may be stored in a computer readable storage medium, or from one
Computer readable storage medium is transmitted to another computer readable storage medium, for example, the computer instruction can be from one
A web-site, computer, server or data center pass through wired (such as coaxial cable, optical fiber, Digital Subscriber Line (DSL)
Or wireless (such as infrared, wireless, microwave etc.) mode is carried out to another web-site, computer, server or data center
Transmission).The computer-readable storage medium can be any usable medium or include one that computer can access
The data storage devices such as a or multiple usable mediums integrated server, data center.The usable medium can be magnetic Jie
Matter, (for example, floppy disk, hard disk, tape), optical medium (for example, DVD) or semiconductor medium (such as solid state hard disk Solid
State Disk (SSD)) etc..
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all in essence of the invention
Made any modifications, equivalent replacements, and improvements etc., should all be included in the protection scope of the present invention within mind and principle.
Claims (10)
1. a kind of control method of server cooling system, which is characterized in that the control method packet of the server cooling system
It includes：
Nonlinear transformation is carried out to received temperature signal s (t) by temperature detecting module, is carried out as follows：
WhereinA is indicated
The amplitude of signal, a (m) indicate that the symbol of signal, p (t) indicate shaping function, fcIndicate the carrier frequency of signal,
Indicate the phase of signal, and by obtaining after the nonlinear transformationCarry out server operating temperature
Data Detection；
Detection service device air quantity of fan data, y (t) are carried out using received air quantity of fan signal y (t) by air volume test module
It is expressed as：
Y (t)=x (t)+n (t)；
Wherein, x (t) is digital modulation signals, and n (t) is the impulsive noise of obedience standard S α S distribution, the analytical form table of x (t)
It is shown as：
Wherein, N is sampling number, anFor the information symbol of transmission, in MASK signal, an=0,1,2 ..., M-1, M are modulation
Order, an=ej2πε/M, ε=0,1,2 ..., M-1, g (t) expression rectangle molding pulse, TbIndicate symbol period, fcIndicate carrier wave
Frequency, carrier wave initial phaseIt is the equally distributed random number in [0,2 π]；
Central control module dispatches air cooling module and carries out cooling down operation by fan blowing；It is carried out by liquid cooled module using liquid
Cooling down operation；
Central control module dispatch air cooling module in, by the server temperature information of collection, server fan air quantity information according to
The quantification gradation of division carries out quantification treatment, and establishes observation evidence table；
The conditional probability transfer matrix between state is established using expertise or experience, determines the state transfer square between time slice
Battle array；
It establishes temperature threat level and influences the discrete dynamic Bayesian network model of temperature factor；
Using observation evidence table, conditional transition probability table and the state transition probability table of foundation, calculated with Hidden Markov reasoning
Method calculates final temperature threat level；Control instruction is issued, air cooling module is scheduled；
By the automatic detection service device hard disk secure state of automatic maintenance module and safeguarded；
Judge whether exception according to temperature, the air quantity data of detection by alarm module, if abnormal and alarm.
2. the control method of server cooling system as described in claim 1, which is characterized in that
The discrete dynamic Bayesian network model is the directed acyclic graph being made of observer nodes and state node, server temperature
Degree, server fan air quantity collectively form discrete state node, and temperature threat level is observer nodes.
3. the control method of server cooling system as described in claim 1, which is characterized in that the observation evidence of the foundation
Table, conditional transition probability table and state transition probability table determine final in conjunction with the discrete dynamic Bayesian network model established
Threat level be that Bayesian inference processes according to a large amount of state node data reasonings go out observer nodes maximum possible value
Probability；
It specifically includes：System parameter λ and observation sequence Y, the process that Forward-backward algorithm infers probability P (Y | λ) are as follows：
Forwards algorithms define forward variable αt(i)=P (y1,y2,...,yt,xt=i | λ)
Initialization：α1(i)=πibi(y1),1≤i≤n
Recursive operation：
As a result：
Backward algorithm, to variable β after definitiont(i)=P (yt+1,yt+2,...,yT|xt=i, λ)
Initialization：βT(i)=1,1≤i≤n
Recursive operation：
As a result：
Forwards algorithms, backward algorithm are combined into composition Forward-backward algorithm：
Finally, according to established observation evidence table, conditional transition probability table and state transition probability table, in conjunction with preceding to-calculation backward
Method infers the temperature threat level of UAV；
The state set of each node indicates that each factor is distinguished with subscript, such as with S in the discrete dynamic Bayesian network model
Shown in lower：
STT={ serious, normal }.
4. the control method of server cooling system as described in claim 1, which is characterized in that air volume detecting method includes：
Firstly, being based respectively on the PWM value for the power supply fan that it currently gets；
Then, according to the power module ventilation quantity Q of the Cabinet-type server pre-established and the respective function of power supply fan PWM value
Relational expression Q=f (PWM)；The current ventilation quantity Q of current server power block to be monitored is calculated, it is current that this can be exported later
Calculate resulting ventilation quantity Q.
5. the control method of server cooling system as described in claim 1, which is characterized in that hard disk automatic maintenance method packet
It includes：
Firstly, the state of detection hard disk；
Then, judge whether the hard disk is abnormal, if the hard disk is abnormal, receive the exception information of the hard disk and in different
Zone position information where the hard disk of normal state, is positioned and is identified to the hard disk in abnormality and be in
The hard disk of abnormality；
Finally, everywhere according to the exception information and the location information of the hard disk in abnormality control robot motion
In the regional location of the hard disk of abnormality；The mark of the hard disk of the robot identification in abnormality, with
The location information of the hard disk in abnormality is obtained, and the hard disk in abnormality is taken out and replaced and is positive
The hard disk often to work.
6. a kind of computer program for realizing the control method of server cooling system described in Claims 1 to 5 any one.
7. a kind of information computer for realizing the control method of server cooling system described in Claims 1 to 5 any one.
8. a kind of computer readable storage medium, including instruction, when run on a computer, so that computer is executed as weighed
Benefit requires the control method of server cooling system described in 1-5 any one.
9. a kind of server cooling system for realizing control method described in claim 1, which is characterized in that the server is cooling
System includes：
Power module is connect with central control module, for being powered to server modules；
Temperature detecting module is connect with central control module, for passing through temperature sensor detection service device operating temperature data；
Air volume test module, connect with central control module, is used for detection service device air quantity of fan data；
Central control module, with power module, temperature detecting module, air volume test module, air cooling module, liquid cooled module, automatic
Maintenance module, alarm module connection, work normally for controlling modules；
Air cooling module is connect with central control module, carries out cooling down operation for drying by fan；
Liquid cooled module is connect with central control module, for carrying out cooling down operation by liquid；
Automatic maintenance module, connect with central control module, for automatic detection service device hard disk secure state and is safeguarded；
Alarm module is connect with central control module, for judging whether exception according to temperature, the air quantity data of detection, if
Abnormal then and alarm.
10. a kind of server for Industry Control for carrying server cooling system described in claim 9.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810732051.1A CN108921223B (en) | 2018-07-05 | 2018-07-05 | Server cooling system, control method, computer program and computer |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810732051.1A CN108921223B (en) | 2018-07-05 | 2018-07-05 | Server cooling system, control method, computer program and computer |
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| Publication Number | Publication Date |
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| CN108921223A true CN108921223A (en) | 2018-11-30 |
| CN108921223B CN108921223B (en) | 2021-12-10 |
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