CN107291030A - A kind of computer room temperature monitoring method - Google Patents
A kind of computer room temperature monitoring method Download PDFInfo
- Publication number
- CN107291030A CN107291030A CN201710619257.9A CN201710619257A CN107291030A CN 107291030 A CN107291030 A CN 107291030A CN 201710619257 A CN201710619257 A CN 201710619257A CN 107291030 A CN107291030 A CN 107291030A
- Authority
- CN
- China
- Prior art keywords
- monitoring system
- record
- alarm
- monitored area
- coefficient
- 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
- 238000012544 monitoring process Methods 0.000 title claims abstract description 56
- 238000000034 method Methods 0.000 title claims abstract description 21
- 238000004458 analytical method Methods 0.000 claims abstract description 26
- 238000004891 communication Methods 0.000 claims abstract description 21
- 238000001514 detection method Methods 0.000 claims abstract description 9
- 230000002123 temporal effect Effects 0.000 claims description 7
- 101001004334 Homo sapiens Protein lin-54 homolog Proteins 0.000 claims description 5
- 102100025692 Protein lin-54 homolog Human genes 0.000 claims description 5
- 101100045632 Arabidopsis thaliana TCX2 gene Proteins 0.000 claims description 4
- 101100045633 Arabidopsis thaliana TCX3 gene Proteins 0.000 claims description 3
- 101000741919 Homo sapiens Activator of RNA decay Proteins 0.000 claims description 3
- 101000848625 Homo sapiens E3 ubiquitin-protein ligase TRIM23 Proteins 0.000 claims description 3
- 101000588230 Homo sapiens N-alpha-acetyltransferase 10 Proteins 0.000 claims description 3
- 101000588232 Homo sapiens N-alpha-acetyltransferase 11 Proteins 0.000 claims description 3
- 102100031641 N-alpha-acetyltransferase 10 Human genes 0.000 claims description 3
- 102100031640 N-alpha-acetyltransferase 11 Human genes 0.000 claims description 3
- 230000001788 irregular Effects 0.000 claims description 3
- 230000009286 beneficial effect Effects 0.000 abstract 1
- 101100366935 Caenorhabditis elegans sto-2 gene Proteins 0.000 description 4
- 101000981375 Homo sapiens Nuclear cap-binding protein subunit 1 Proteins 0.000 description 4
- 102100024372 Nuclear cap-binding protein subunit 1 Human genes 0.000 description 4
- 238000001816 cooling Methods 0.000 description 4
- 238000013528 artificial neural network Methods 0.000 description 2
- 235000013399 edible fruits Nutrition 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 230000006870 function Effects 0.000 description 2
- 238000005070 sampling Methods 0.000 description 2
- 101100366936 Caenorhabditis elegans sto-3 gene Proteins 0.000 description 1
- 101100366937 Caenorhabditis elegans sto-4 gene Proteins 0.000 description 1
- 208000033999 Device damage Diseases 0.000 description 1
- 230000000977 initiatory effect Effects 0.000 description 1
- 230000000737 periodic effect Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
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
- G05B19/048—Monitoring; Safety
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01K—MEASURING TEMPERATURE; MEASURING QUANTITY OF HEAT; THERMALLY-SENSITIVE ELEMENTS NOT OTHERWISE PROVIDED FOR
- G01K1/00—Details of thermometers not specially adapted for particular types of thermometer
- G01K1/02—Means for indicating or recording specially adapted for thermometers
- G01K1/026—Means for indicating or recording specially adapted for thermometers arrangements for monitoring a plurality of temperatures, e.g. by multiplexing
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Automation & Control Theory (AREA)
- Alarm Systems (AREA)
Abstract
The invention discloses a kind of computer room temperature monitoring method, it includes creating monitoring system analysis object；Monitoring system communication object is created for each temperature monitoring node, and operation is named to monitoring system communication object；The monitored area object in monitoring system is defined by region, each monitored area includes the temperature detection node；Set up the corresponding relation of the monitoring system communication object and the monitored area object；Each temperature detection node data is obtained by the monitoring system communication object in real time, and is saved in database；The database is analyzed, judges whether to need to propose alarm or sends pre-alert notification.The beneficial effect that the present invention is obtained：A kind of effective early warning mechanism can be set up, when temperature will reach early warning value, pre-alert notification is sent.
Description
Technical field
The present invention relates to room environment monitoring technical field, particularly a kind of computer room temperature monitoring method.
Background technology
It is the need of Safeguard Informatization Establishment with the progressively release of smart city with developing rapidly for informationization technology
Will be, it is necessary to which the equipment set up in substantial amounts of central machine room, computer room turns into the necessary support of informatization, if calculator room equipment is transported
Row is unstable or even often breaks down, and will cause larger direct and indirect economic loss, so ensureing calculator room equipment
Stable operation, an emphasis as informatization.During calculator room equipment is run, substantial amounts of heat, temperature mistake can be produced
Height easily causes device damage, so as to cause direct and indirect economic loss.In traditional processing, only temperature parameter is carried out
Collection, but have no intelligentized analysis and management, in order to prevent temperature is too high from causing damage, otherwise always on cooling system
The wasting of resources is caused, otherwise artificial periodic operation cooling system, can not effectively guard against and solve the problems, such as.
The content of the invention
In view of the drawbacks described above of prior art, it is an object of the invention to provide a kind of computer room temperature monitoring method, energy
A kind of effective early warning mechanism is enough set up, when temperature will reach early warning value, pre-alert notification is sent.
The purpose of the present invention realized by such technical scheme, a kind of computer room temperature monitoring method, and it includes：
The computer room temperature monitoring method step is as follows：
S1：Create monitoring system analysis object；
S2：Monitoring system communication object is created for each temperature monitoring node, and monitoring system communication object is ordered
Name operation；
S3：The monitored area object in monitoring system is defined by region, each monitored area includes the temperature detection
Node；
S4：Set up the corresponding relation of the monitoring system communication object and the monitored area object；
S5：Each temperature detection node data is obtained by the monitoring system communication object in real time, and is saved in database
In；
S6：Database described in analytical procedure S5, judges whether to need to propose alarm or sends pre-alert notification.
Further, monitoring system analysis object is ZXO in step S1, and the parameter that acquirement system is set includes：Moment be
Number TCX, error deviation amount VC0, alarm index WC, temporal scalability COEFFICIENT K.
Further, the data described in step S5 in database include：Record information includes：Time RecT, temperature C,
Section object numbering JIOID.
Further, propose that the specific method for alarming or sending early warning is as follows described in step S6：
S61：Moment coefficient T CX is set, it is ensured that every group of data at least one temperature C value in each monitored area；Such as
There is no the record in certain region in fruit moment coefficient T CX, then ignore the field when calculating；
S62：Current Temperatures C1 is obtained, if C1 is more than alarm index WC, alarm is proposed, step is terminated, conversely, then continuing
Follow the steps below；
S63：Analysis object ZXO takes record data in moment coefficient T CX nearest a cycle, be respectively designated as AR1,
AR2 ... ARN, a record of a monitored area is corresponded to respectively；The temperature parameter Cc of every record is obtained, if certain note
The Cc values of record are more than alarm index WC, then propose alarm, step is terminated, conversely, then proceeding following steps；
S64：Each record at the time of searching one day synchronization in coefficient T CX, respectively ARD1, ARD2,
... ARDN, a record of a monitored area is corresponded to respectively；The temperature parameter Cd of every record is obtained, if each monitoring
Always have in region | Cd-Cc |<VC0, then find and coefficient at the time of upper one day, synchronization was close in nearest a cycle
TCX, is designated as TCX1；
S65：Repeat step 6-4), find out in nearest a cycle with coefficient T CX at the time of upper one day, synchronization was close,
Be designated as respectively TCX2, TCX3 ... TCXN；
S66：The TCX for alarm logging occur is searched, and records the time Tc for alarm logging occur；
S67：Tc is subjected to classification processing, the Tc close with synchronization upper one day will be found in a cycle recently and returned
In one-level, then by how much divided ranks of middle Tc quantity at different levels, quantity it is most for 1 grade, be secondly 2 grades, until N grades；
S68：Early warning report is submitted by grade.
Further, in step S67, during classification processing, calculate in the time difference △ T that Tc and TCX is recorded, nearest a cycle
± K is not to be exceeded in the time difference △ T close with synchronization upper one day difference, and K is temporal scalability coefficient.
Further, the region division rule described in step S3 is to be divided into irregular area by calculator room equipment management requirement
Or by mesh generation be regular domain.
By adopting the above-described technical solution, the present invention has the advantage that：The present invention is supervised different from traditional temperature
Survey method, the application introduces genetic-neural network algorithm and area grid algorithm on the basis of data sampling, the logarithm from space-time
According to intellectual analysis has been carried out, so as to timely alarm and following data are predicted so that monitoring system has in itself
There is intelligence learning function, and each region is organically combined into comprehensive analysis, so, as the time that system is used is longer,
Predicted value is more accurate, so as to help computer room efficiently to manage cooling system, both economizes on resources, and ensures that the safety of calculator room equipment can again
Lean on.
Other advantages, target and the feature of the present invention will be illustrated in the following description to a certain extent, and
And to a certain extent, based on will be apparent to those skilled in the art to investigating hereafter, Huo Zheke
To be instructed from the practice of the present invention.The target and other advantages of the present invention can be wanted by following specification and right
Book is sought to realize and obtain.
Brief description of the drawings
The brief description of the drawings of the present invention is as follows：
Fig. 1 is structural representation of the invention.
Fig. 2 is FB(flow block) of the invention.
Fig. 3 is moment coefficient T CX records and alarm decision flow chart in the nearest a cycle of the present invention.
Fig. 4 for the present invention lookup daily in the same time at the time of coefficient T CX flow charts.
Fig. 5 is each moment coefficient T CX time of fire alarming flow charts of lookup of the invention.
Fig. 6 is classified flow chart for the Tc of the present invention.
Embodiment
The invention will be further described with reference to the accompanying drawings and examples.
Embodiment 1：As shown in Figures 1 to 6；A kind of computer room temperature monitoring method, it includes：The computer room temperature monitoring
Method and step is as follows：
S1：Create monitoring system analysis object ZXO；
S2：A monitoring system communication object is created for each temperature monitoring node, and monitoring system communication object is entered
Row naming operation；Be respectively designated as STO1, STO2 ... STON；
S3：The monitored area object in monitoring system is defined by region, each monitored area includes the temperature detection
Node；Monitored area object be respectively designated as JFO1, JFO2 ... JFON；Wherein region is divided into by calculator room equipment management requirement
Irregular area is regular domain by mesh generation, is included and only one temperature detection node in each region；
S4：Set up the corresponding relation of the monitoring system communication object and the monitored area object；Such as STO1 and JFO3,
STO2 is corresponding with JFO5 etc., until completing all one-to-one relations；
S5：Each temperature detection node data is obtained by monitoring system communication object STO1 to the STON in real time, and protected
It is stored in database；
S6：Database described in analytical procedure S5, judges whether to need to propose alarm or sends pre-alert notification.
Monitoring system analysis object is ZXO in step S1, and the parameter that acquirement system is set includes：Moment coefficient T CX, mistake
Poor offset VC0, alarm index WC, temporal scalability COEFFICIENT K.
Data described in step S5 in database include：Record information includes：Time RecT, temperature C, section object
Numbering JIOID.
Propose that the specific method for alarming or sending early warning is as follows described in step S6：
S61：Moment coefficient T CX is set, it is ensured that every group of data at least one temperature C value in each monitored area；Such as
There is no the record in certain region in fruit moment coefficient T CX, then ignore the field when calculating；
S62：Current Temperatures C1 is obtained, if C1 is more than alarm index WC, alarm is proposed, step is terminated, conversely, then continuing
Follow the steps below；
S63：Analysis object ZXO takes record data in moment coefficient T CX nearest a cycle, be respectively designated as AR1,
AR2 ... ARN, a record of a monitored area is corresponded to respectively；The temperature parameter Cc of every record is obtained, if certain note
The Cc values of record are more than alarm index WC, then propose alarm, step is terminated, conversely, then proceeding following steps；
S64：Each record at the time of searching one day synchronization in coefficient T CX, respectively ARD1, ARD2,
... ARDN, a record of a monitored area is corresponded to respectively；The temperature parameter Cd of every record is obtained, if each monitoring
Always have in region | Cd-Cc |<VC0, then find and coefficient at the time of upper one day, synchronization was close in nearest a cycle
TCX, is designated as TCX1；
S65：Repeat step 6-4), find out in nearest a cycle with coefficient T CX at the time of upper one day, synchronization was close,
Be designated as respectively TCX2, TCX3 ... TCXN；
S66：The TCX for alarm logging occur is searched, and records the time Tc for alarm logging occur；
S67：Tc is subjected to classification processing, the Tc close with synchronization upper one day will be found in a cycle recently and returned
In one-level, then by how much divided ranks of middle Tc quantity at different levels, quantity it is most for 1 grade, be secondly 2 grades, until N grades；
S68：By grade submit early warning report because 1 grade quantity at most, 1 grade for be most likely to occur alarm when
Between.
In step S67, during classification processing, calculate in the time difference △ T that Tc and TCX are recorded, nearest a cycle with upper one
± K is not to be exceeded in the close time difference △ T of its synchronization difference, and K is temporal scalability coefficient.
As shown in figure 1, there is 4 monitoring nodes in computer room, be respectively divided to 4 monitored areas, correspond to JFO1, JFO2,
JFO3、JFO4.Monitoring system sets up 4 communication objects and obtains temperature parameter, 4 communications pair from monitoring node by traffic operation
As being respectively STO1, STO2, STO3, STO4.The temperature parameter that intellectual analysis object ZXO is gathered according to communication object carries out intelligence
Analysis.
System sets coefficient T CX=2 minutes moment, error deviation amount VC0=0.2, alarm index WC=60, temporal scalability
COEFFICIENT K=5 minute.
When existing communication object STO2 obtains a record from the JFO2 of monitored area, intellectual analysis object ZXO presses Fig. 2 flows
Handled.
Intellectual analysis object ZXO obtains communication object JFO2 temperature C1 first, if temperature C1 numerical value is more than alarm
Coefficient WC numerical value, then intellectual analysis object ZXO initiations alarm.If not possessing alert if, intellectual analysis object ZXO starts
Carry out early warning calculating.
Intellectual analysis object ZXO is obtained the record data in moment coefficient T CX nearest a cycle by Fig. 3, is named respectively
For AR1, AR2 ... ARN, one of monitored area record is corresponded to respectively；The temperature parameter Cc of every record is obtained, if
The Cc values of certain record are more than alarm index WC, then propose alarm, and step is terminated, and no longer carries out early warning calculating；Conversely, then press with
Lower step proceeds early warning calculating.
If do not alarmed in the nearest coefficient T CX cycles at a moment, intellectual analysis object ZXO proceeds early warning
Processing.
ZXO searches each day similar TCX in the same time by Fig. 4, be denoted as TCX1, TCX2 ..., TCXN, and by Fig. 5 search from
TCX1 to TCXN alarm logging, obtain alarm logging time of fire alarming, respectively Tc1, Tc2 ..., TcN.Fig. 6 is pressed again by Tc
Classification processing is carried out, and each DBMS obtained by classification sends early warning report.
The device have the advantages that：A kind of effective early warning mechanism can be set up, early warning value will be reached in temperature
When, send pre-alert notification；The present invention is different from traditional temperature monitoring method, and the application is introduced on the basis of data sampling
Data have been carried out intellectual analysis, so as to timely alarm by genetic-neural network algorithm and area grid algorithm from space-time
And following data are predicted so that monitoring system has intelligence learning function in itself, and each region is organically combined
Get up comprehensive analysis, so, as the time that system is used is longer, predicted value is more accurate, so as to help computer room efficiently to manage
Cooling system, was both economized on resources, and the safe and reliable of calculator room equipment is ensured again.
Finally illustrate, the above embodiments are merely illustrative of the technical solutions of the present invention and it is unrestricted, although with reference to compared with
The present invention is described in detail good embodiment, it will be understood by those within the art that, can be to skill of the invention
Art scheme is modified or equivalent substitution, and without departing from the objective and scope of the technical program, it all should cover in the present invention
Right among.
Claims (6)
1. a kind of computer room temperature monitoring method, it is characterised in that：The computer room temperature monitoring method step is as follows：
S1：Create monitoring system analysis object；
S2：Monitoring system communication object is created for each temperature monitoring node, and behaviour is named to monitoring system communication object
Make；
S3：The monitored area object in monitoring system is defined by region, each monitored area includes the temperature detection node；
S4：Set up the corresponding relation of the monitoring system communication object and the monitored area object；
S5：Each temperature detection node data is obtained by the monitoring system communication object in real time, and is saved in database；
S6：Database described in analytical procedure S5, judges whether to need to propose alarm or sends pre-alert notification.
2. computer room temperature monitoring method as claimed in claim 1, it is characterised in that：Monitoring system analysis object is in step S1
ZXO, the parameter that acquirement system is set includes：Moment coefficient T CX, error deviation amount VC0, alarm index WC, temporal scalability system
Number K.
3. computer room temperature monitoring method as claimed in claim 2, it is characterised in that：Data described in step S5 in database
Include：Record information includes：Time RecT, temperature C, section object numbering JIOID.
4. computer room temperature monitoring method as claimed in claim 3, it is characterised in that：Alarm is proposed described in step S6 or is sent
The specific method of early warning is as follows：
S61：Moment coefficient T CX is set, it is ensured that every group of data at least one temperature C value in each monitored area；If when
Carving in coefficient T CX does not have the record in certain region, then ignores the field when calculating；
S62：Current Temperatures C1 is obtained, if C1 is more than alarm index WC, alarm is proposed, step is terminated, conversely, then proceeding
Following steps；
S63：Analysis object ZXO takes record data in moment coefficient T CX nearest a cycle, be respectively designated as AR1,
AR2 ... ARN, a record of a monitored area is corresponded to respectively；The temperature parameter Cc of every record is obtained, if certain note
The Cc values of record are more than alarm index WC, then propose alarm, step is terminated, conversely, then proceeding following steps；
S64：Each record at the time of searching one day synchronization in coefficient T CX, respectively ARD1, ARD2 ... ARDN, point
Dui Ying not one of monitored area record；The temperature parameter Cd of every record is obtained, if always had in each monitored area |
Cd-Cc|<VC0, then found in nearest a cycle with coefficient T CX at the time of upper one day, synchronization was close, be designated as TCX1；
S65：Repeat step 6-4), find out in nearest a cycle with coefficient T CX at the time of upper one day, synchronization was close, respectively
Be designated as TCX2, TCX3 ... TCXN；
S66：The TCX for alarm logging occur is searched, and records the time Tc for alarm logging occur；
S67：Tc is subjected to classification processing, will finding the Tc close with synchronization upper one day in a cycle be attributed to one recently
Level, then by how much divided ranks of middle Tc quantity at different levels, quantity it is most for 1 grade, be secondly 2 grades, until N grades；
S68：Early warning report is submitted by grade.
5. computer room temperature monitoring method as claimed in claim 4, it is characterised in that：In step S67, during classification processing, calculate
The time difference △ T that Tc and TCX is recorded, the interior time difference △ T close with synchronization upper one day of nearest a cycle difference is not
± K should be exceeded, K is temporal scalability coefficient.
6. computer room temperature monitoring method as claimed in claim 1, it is characterised in that：Region division rule described in step S3
To be divided into irregular area by calculator room equipment management requirement or being regular domain by mesh generation.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710619257.9A CN107291030B (en) | 2017-07-26 | 2017-07-26 | A kind of computer room temperature monitoring method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710619257.9A CN107291030B (en) | 2017-07-26 | 2017-07-26 | A kind of computer room temperature monitoring method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN107291030A true CN107291030A (en) | 2017-10-24 |
| CN107291030B CN107291030B (en) | 2019-09-24 |
Family
ID=60102815
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710619257.9A Active CN107291030B (en) | 2017-07-26 | 2017-07-26 | A kind of computer room temperature monitoring method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107291030B (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110237477A (en) * | 2019-01-25 | 2019-09-17 | 江苏沃德渥机电科技有限公司 | A kind of firefighting monitoring system based on artificial intelligence |
| CN110568293A (en) * | 2019-09-27 | 2019-12-13 | 广东电网有限责任公司 | Monitoring method and system for power equipment |
| CN111240943A (en) * | 2020-04-28 | 2020-06-05 | 成都派沃特科技股份有限公司 | Method, device and equipment for monitoring temperature of machine room and storage medium |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101441798A (en) * | 2008-03-05 | 2009-05-27 | 中科院嘉兴中心微系统所分中心 | Safe monitoring and emergency commanding and controlling system based on wireless sensor network |
| CN203799236U (en) * | 2014-01-07 | 2014-08-27 | 淮安信息职业技术学院 | Embedded type Zigbee monitoring node and greenhouse factor monitoring system |
| CN104408851A (en) * | 2014-11-26 | 2015-03-11 | 浙江中南智能科技有限公司 | Intelligent cell safety monitoring and controlling system based on Internet of Things |
| CN104678954A (en) * | 2015-01-23 | 2015-06-03 | 中国长江三峡集团公司 | Dam safety intelligent monitoring and pre-warning system based on full life circle and method thereof |
| CN105632114A (en) * | 2015-12-30 | 2016-06-01 | 上海顺凯信息技术股份有限公司 | Monitoring measurement point safety state monitoring method based on GIS technology |
-
2017
- 2017-07-26 CN CN201710619257.9A patent/CN107291030B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101441798A (en) * | 2008-03-05 | 2009-05-27 | 中科院嘉兴中心微系统所分中心 | Safe monitoring and emergency commanding and controlling system based on wireless sensor network |
| CN203799236U (en) * | 2014-01-07 | 2014-08-27 | 淮安信息职业技术学院 | Embedded type Zigbee monitoring node and greenhouse factor monitoring system |
| CN104408851A (en) * | 2014-11-26 | 2015-03-11 | 浙江中南智能科技有限公司 | Intelligent cell safety monitoring and controlling system based on Internet of Things |
| CN104678954A (en) * | 2015-01-23 | 2015-06-03 | 中国长江三峡集团公司 | Dam safety intelligent monitoring and pre-warning system based on full life circle and method thereof |
| CN105632114A (en) * | 2015-12-30 | 2016-06-01 | 上海顺凯信息技术股份有限公司 | Monitoring measurement point safety state monitoring method based on GIS technology |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110237477A (en) * | 2019-01-25 | 2019-09-17 | 江苏沃德渥机电科技有限公司 | A kind of firefighting monitoring system based on artificial intelligence |
| CN110568293A (en) * | 2019-09-27 | 2019-12-13 | 广东电网有限责任公司 | Monitoring method and system for power equipment |
| CN111240943A (en) * | 2020-04-28 | 2020-06-05 | 成都派沃特科技股份有限公司 | Method, device and equipment for monitoring temperature of machine room and storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN107291030B (en) | 2019-09-24 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108564254B (en) | Big data-based power distribution equipment status visualization platform | |
| Stolpe | The internet of things: Opportunities and challenges for distributed data analysis | |
| KR101981310B1 (en) | Apparatus and method for detecting anomaly of database system | |
| CN111190876A (en) | Log management system and operation method thereof | |
| KR101761781B1 (en) | Big data processing method for applying integrated management framework for the open source database | |
| CN107612779B (en) | Secondary safety protection network equipment of dispatching data network and service operation monitoring system | |
| CN105005274A (en) | Managing big data in process control systems | |
| KR102097453B1 (en) | Programmable Logic Controller pattern analysis system for improving lifetime and productivity of factory automation facilities, and method thereof | |
| CN105659528A (en) | Method and apparatus for realizing fault location | |
| Nasridinov et al. | Event detection in wireless sensor networks: Survey and challenges | |
| CN117453137A (en) | Cloud intelligent operation and maintenance system data management system | |
| CN107291030B (en) | A kind of computer room temperature monitoring method | |
| CN118713927B (en) | An information security asset cyberspace mapping system | |
| Tran et al. | Change detection in streaming data in the era of big data: models and issues | |
| CN103581198A (en) | Security log analyzing method based on Apriori algorithm | |
| CN118842190B (en) | Intelligent monitoring method and system for group distribution cabinets based on highly integrated power modules | |
| CN116436821A (en) | Operation and maintenance management software system based on artificial intelligent computing platform | |
| CN102521378A (en) | Real-time intrusion detection method based on data mining | |
| CN119341788A (en) | A network resource intrusion detection method combined with big data analysis | |
| CN106445973B (en) | The monitoring method and device of search engine | |
| CN112784129A (en) | Pump station equipment operation and maintenance data supervision platform | |
| CN115277249B (en) | Network security situation perception method based on cooperation of multi-layer heterogeneous network | |
| Dong et al. | Design of Network Security Situation Awareness and Early Warning System Based on Big Data | |
| Dagnely et al. | A semantic model of events for integrating photovoltaic monitoring data | |
| CN115510467A (en) | Agricultural environment data anomaly detection and security management method |
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 | ||
| TR01 | Transfer of patent right | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20200509 Address after: No. 71, No. 1, No. 15, beichengtian street, Jiangbei District, Chongqing Patentee after: Chongqing Yuandun Technology Group Co.,Ltd. Address before: 400039 Jiulongpo District of Chongqing Science Park Road 166, Torch Hotel, No. 2 building 10-2 Patentee before: CHONGQING QICAIHONG DIGITAL TECHNOLOGY Co.,Ltd. |
|
| TR01 | Transfer of patent right | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20220620 Address after: Room 10-2, building 2, Torch Building, No. 166, Keyuan 1st Road, Jiulongpo District, Chongqing 400039 Patentee after: CHONGQING QICAIHONG DIGITAL TECHNOLOGY CO.,LTD. Address before: 400020 No.71, no.15-1, beichengtian street, Jiangbei District, Chongqing Patentee before: Chongqing Yuandun Technology Group Co.,Ltd. |