CN110287347A - Using the method for big data detection electric power computer room failure - Google Patents
Using the method for big data detection electric power computer room failure Download PDFInfo
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Abstract
Using the method for big data detection electric power computer room failure, it is related to computer room detection technique field.The present invention is the abnormality monitoring method in order to solve existing computer room, be easy there is a problem of slip, can not find the problem in time and can not accurate judgement computer room state cause maintenance efficiency low.Method of the present invention using big data detection electric power computer room failure, the abnormality picture of computer room is acquired by big data, is referred to as a comparison, information is more comprehensive, and comparing result is relatively reliable；It replicates multiple identical comparisons collection and is synchronized respectively with state set and is compared, so that comparing speed faster, can timely obtain current information, more efficiently；Since state has carried out state classification first, then it is capable of the classification of direct lockout issue after comparing similarity；Package can in real time be monitored the state in computer room, find the problem much sooner, the monitoring suitable for all computer rooms.
Description
Technical field
The invention belongs to computer room detection technique fields.
Background technique
Power scheduling is to guarantee that power network safety operation, external reliable power supply, the work of all kinds of power generations are orderly
A kind of effective management means for carrying out and using.The specific works content of power scheduling is anti-according to various information acquisition equipment
Be fed back to the data information come or information that monitoring personnel provides, in conjunction with power grid actual operation parameters, as voltage, electric current, frequency,
Load etc. comprehensively considers every production work development condition, judges power grid security, economical operation state, passes through phone
Or automatic system issues operational order, commander site operation personnel or automatic control system are adjusted, and are such as adjusted generator and are gone out
Power, Load adjustment distribution, switched capacitor, reactor etc., so that it is guaranteed that power grid continues safe and stable operation.Therefore, electric power tune
Degree computer room needs to guarantee at runtime safety and steady, otherwise once breaking down, it will leads to power-off, load increase, voltage not
The problems such as stablizing.
It is at present video monitoring or sensor alarm to the abnormality monitoring method of power scheduling computer room.In computer room, example
Such as the problems such as temperature, humidity, smog dust, corresponding sensor real-time monitoring can be used and obtain.But as ageing equipment or
The problems such as fracture is then cannot be directly detected by sensor.For problems, a kind of mode is at supervision object
Monitoring of the video camera realization to equipment and its operating condition is installed.But artificial monitoring requirement staff is always before screen,
Not only heavy workload, and inevitably have careless omission.Another way is that staff periodically carries out inspection, and regularly checks not
Can play the role of real time monitoring, cause it is problematic can not find in time, just have such as route loosen, aging or attachment
Dust causes device temperature to increase, generates the generation of phenomena such as smog in turn.Although these phenomenons can pass through sensing after occurring
Device collects corresponding signal, and still, sensor can only reflect the presentation of problem after deterioration, can not inform staff's problem
It is basic, staff does not know the time of day of computer room, it is necessary to first check problem, can waste the plenty of time at this time.
To sum up, for the security monitoring of power scheduling computer room, there is also many masty problems at present.
Summary of the invention
The present invention is the abnormality monitoring method in order to solve existing computer room, is easy to have careless omission, can not find to ask in time
Topic and can not the accurate judgement computer room state problem that causes maintenance efficiency low, now provide and electric power computer room detected using big data
The method of failure.
Using the method for big data detection electric power computer room failure, comprising the following steps:
Step 1: property data base is established using the data in network large database concept, includes n class in this feature database
The abnormality collection of type and 1 normal condition collection；
Step 2: the picture of acquisition computer room position to be judged and the feature conduct detection collection for extracting the picture, then replicate n
A identical detection collection, obtains n+1 detection collection altogether；
Step 3: n+1 detection collection is corresponded with n+1 state set in property data base respectively, will be corresponding
Detection collection and state set as a control group, calculate the similarity of detection collection and state set in each control group, obtain n+1
A similarity result；
Step 4: judge whether maximum value is greater than 80% in n+1 similarity result, be to then follow the steps five, otherwise hold
Row step 6；
Step 5: by the group as a result of control group corresponding to similarity maximum value, by the state of state set in result group
As computer room state, when the computer room state is abnormality, emergency alarm is sent to computer room control centre, simultaneously by machine
Room state is also sent to computer room control centre；
Step 6: judge whether maximum value is greater than 50% in n+1 similarity result, be to then follow the steps seven, otherwise hold
Row step 8；
Step 7: by the group as a result of control group corresponding to similarity maximum value, by the state of state set in result group
As computer room state, when the computer room state is abnormality, send to computer room control centre there are hidden danger signal, simultaneously by machine
Room state is also sent to computer room control centre；
Step 8: to computer room control centre sends abnormal help signal, the picture simultaneously by step 2 acquisition is sent to machine
Room control centre judges computer room state according to picture by technical staff, then executes step 9；
Step 9: whether the judging result that judgment step eight obtains belongs to state corresponding to normal condition collection, then will be
The element deposit normal condition that detection is concentrated is concentrated, and step 10 is otherwise executed；
Step 10: whether the judging result that judgment step eight obtains belongs to state corresponding to n abnormality collection, is then
The element that will test concentration is stored in corresponding abnormality and concentrates, and otherwise executes step 11；
Step 11: it will test in the abnormality collection deposit property data base for collecting new as one.
In step 5 and step 7 using the state of state set in result group as computer room state after, equal return step two
The computer room state of subsequent time is judged；
Phase is stored in the element that step 9 will test the element deposit normal condition collection of concentration and step 10 will test concentration
After the abnormality collection answered, property data base is updated, then computer room state of the return step two to subsequent time
Judged；
After step 11, property data base is updated, makes n=n+1, then computer room of the return step two to subsequent time
State is judged.
In step 3, detection collection and the similarity of state set in each control group are calculated method particularly includes:
The each element that will test concentration compares with each element in state set respectively and obtains the phase between element
Like angle value, using similarity value maximum between element as the similarity of detection collection and state set.
In step 1, property data base is established method particularly includes:
The picture in computer room under various abnormalities in position to be judged is acquired in network large database concept, extracts each picture
Feature and using feature corresponding to same Exception Type state as an abnormality set, obtain the exception of n type
State set,
The picture in computer room under position normal condition to be judged is acquired in network large database concept, is acquired wait judge in computer room
Picture under position normal condition to be judged, extracts the picture feature under each normal condition, as normal condition set,
Property data base is established using n abnormality set and normal condition set.
After property data base is established in step 1, property data base is uploaded in block chain.
After property data base updates, updated property data base is uploaded in block chain.
Method of the present invention using big data detection electric power computer room failure, the exception of computer room is acquired by big data
State picture, refers to as a comparison, and information is more comprehensive, and comparing result is relatively reliable；Replicate multiple identical comparison collection difference
It synchronizes and is compared with state set, so that comparing speed faster, can timely obtain current information, more efficiently；Due to shape
State has carried out state classification first, then is capable of the classification of directly lockout issue after comparing similarity, and staff can the
One time learnt the root of problem, provides effective information to the subsequent maintenance of staff and assists；Package can be real
When the state in computer room is monitored, it is more efficient, find the problem much sooner, the monitoring suitable for all computer rooms.
Detailed description of the invention
Fig. 1 is the flow chart for detecting the method for electric power computer room failure described in specific embodiment one using big data.
Specific embodiment
Specific embodiment 1: present embodiment is illustrated referring to Fig.1, the inspection of use big data described in present embodiment
The method for surveying electric power computer room failure, comprising the following steps:
Step 1: the picture in computer room under various abnormalities in position to be judged is acquired in network large database concept, is extracted
The feature of each picture and using feature corresponding to same Exception Type state as an abnormality set, obtains n class
The abnormality set of type,
The picture in computer room under position normal condition to be judged is acquired in network large database concept, is acquired wait judge in computer room
Picture under position normal condition to be judged, extracts the picture feature under each normal condition, as normal condition set,
Property data base is established using n abnormality set and normal condition set.
In the above step 1, material is acquired in network large database concept to refer to as a comparison, these network large database concepts
In data class multiplicity, to it is subsequent comparison and judgement provide more comprehensive basis.Also, in advance by Status Type point
Class convenient for subsequent contrast and determines type at collection.
Step 2: the picture of acquisition computer room position to be judged and the feature conduct detection collection for extracting the picture, then replicate n
A identical detection collection, obtains n+1 detection collection altogether.
Step 3: n+1 detection collection is corresponded with n+1 state set in property data base respectively, will be corresponding
Detection collection and state set as a control group；
In control group, each element that will test concentration is compared and is obtained with each element in state set respectively
The similarity value between element is obtained, using similarity value maximum between element as the similarity of detection collection and state set, obtains n+1 altogether
The similarity result of a comparison collection and state set.
In above-mentioned steps two, then comparison collection duplication is existed so that the quantity of comparison collected works is equal with the quantity of state set
Compared correspondingly in step 3.The mode that compared to one comparison collection is compared with multiple state sets respectively, section
About the time, improve work efficiency.Further, since set in element quantity it is more, if comparison concentrate an element with
An element in state set is identical, then proves the state consistency of position and state set to be judged.But if comparison is collected
Element in as soon as is integrally compared with state set, then similarity will be greatly reduced, for after all it is not possible that and each
A state set element is all identical, therefore will lead to the problem of result inaccuracy.In step 3, element and element are carried out pair
Than, then using maximum similarity value as the similarity result between set and set, be only so most true as a result, last
Judging result it is also more accurate.
Step 4: judge whether maximum value is greater than 80% in n+1 similarity result, be to then follow the steps five, otherwise hold
Row step 6；
Step 5: by the group as a result of control group corresponding to similarity maximum value, by the state of state set in result group
As computer room state, when the computer room state is abnormality, emergency alarm is sent to computer room control centre, simultaneously by machine
Room state is also sent to computer room control centre；
Step 6: judge whether maximum value is greater than 50% in n+1 similarity result, be to then follow the steps seven, otherwise hold
Row step 8；
Step 7: by the group as a result of control group corresponding to similarity maximum value, by the state of state set in result group
As computer room state, when the computer room state is abnormality, send to computer room control centre there are hidden danger signal, simultaneously by machine
Room state is also sent to computer room control centre；
Step 8: to computer room control centre sends abnormal help signal, the picture simultaneously by step 2 acquisition is sent to machine
Room control centre judges computer room state according to picture by technical staff, then executes step 9；
Step 9: whether the judging result that judgment step eight obtains belongs to state corresponding to normal condition collection, then will be
The element deposit normal condition that detection is concentrated is concentrated, and step 10 is otherwise executed；
Step 10: whether the judging result that judgment step eight obtains belongs to state corresponding to n abnormality collection, is then
The element that will test concentration is stored in corresponding abnormality and concentrates, and otherwise executes step 11；
Step 11: it will test in the abnormality collection deposit property data base for collecting new as one.
In above-mentioned steps four, when the maximum value in similarity result is greater than 80%, then position to be judged can determine
State is that the probability of the state of state set is very big, then can be by step 5 using the state of state set in result group as computer room
State, to complete the state judgement at current time.
In above-mentioned steps four, when the maximum value in similarity result is less than 80%, then position to be judged can determine
State and the state of state set in feature database less meet, then just needing further to judge by step 6, work as similarity
As a result greater than 50% and when result group state is abnormality, then prove there is abnormal hidden danger.When similarity result is less than 50%
When, then need step 8 to seek help to control centre, it may be assumed that by technical staff's artificial judgment.Although this step is also required to using artificial
Judgement, still, due to having been judged by big data in above-mentioned steps, then just illustrating the state of position to be judged is
A kind of special state that probability of occurrence is extremely low or new state, since what such state occurred lacks, then step 8 is triggered
Probability also will accordingly reduce, necessarily also reduce the probability of artificial judgment；And just meeting when only state occurs
Notify staff, not needing staff's moment monitors, and greatly reduces the workload of staff.
After step 8 artificial judgment, it will be able to Status Type is determined, if the Status Type is state in property data base
The corresponding type of collection, element is just directly stored in corresponding state collection by that.If the Status Type is shape in property data base
Type corresponding to state collection, then prove new type occur, and the type necessarily Exception Type, then in property data base
One new abnormality collection of middle increase, so that n=n+1, property data base is updated, so that data therein more add
It is whole, improve subsequent judging nicety rate.
Moreover, after property data base obtains update, updated property data base is uploaded to block in above-mentioned steps
In chain, information sharing, once a certain system failure, can also find database in block chain, subsequent detection is protected.
Claims (6)
1. using the method for big data detection electric power computer room failure, which comprises the following steps:
Step 1: property data base is established using the data in network large database concept, includes n type in this feature database
Abnormality collection and 1 normal condition collection；
Step 2: the picture of acquisition computer room position to be judged and the feature conduct detection collection for extracting the picture, then replicate n phase
Same detection collection obtains n+1 detection collection altogether；
Step 3: n+1 detection collection is corresponded with n+1 state set in property data base respectively, by corresponding inspection
The similarity of collection and state set as detection collection and state set in a control group, each control group of calculating is surveyed, n+1 phase is obtained
Like degree result；
Step 4: judge whether maximum value is greater than 80% in n+1 similarity result, be to then follow the steps five, otherwise execute step
Rapid six；
Step 5: by the group as a result of control group corresponding to similarity maximum value, using the state of state set in result group as
Computer room state sends emergency alarm to computer room control centre, simultaneously by computer room shape when the computer room state is abnormality
State is also sent to computer room control centre；
Step 6: judge whether maximum value is greater than 50% in n+1 similarity result, be to then follow the steps seven, otherwise execute step
Rapid eight；
Step 7: by the group as a result of control group corresponding to similarity maximum value, using the state of state set in result group as
Computer room state is sent to computer room control centre there are hidden danger signal, simultaneously by computer room shape when the computer room state is abnormality
State is also sent to computer room control centre；
Step 8: to computer room control centre sends abnormal help signal, the picture simultaneously by step 2 acquisition is sent to computer room control
Center processed judges computer room state according to picture by technical staff, then executes step 9；
Step 9: whether the judging result that judgment step eight obtains belongs to state corresponding to normal condition collection, is that will test
The element deposit normal condition of concentration is concentrated, and step 10 is otherwise executed；
Step 10: whether the judging result that judgment step eight obtains belongs to state corresponding to n abnormality collection, and being then will inspection
It surveys the element concentrated and is stored in corresponding abnormality concentration, otherwise execute step 11；
Step 11: it will test in the abnormality collection deposit property data base for collecting new as one.
2. the method according to claim 1 using big data detection electric power computer room failure, which is characterized in that
In step 5 and step 7 using the state of state set in result group as computer room state after, equal return step two is under
The computer room state at one moment is judged；
It is corresponding in the element deposit that step 9 will test the element deposit normal condition collection of concentration and step 10 will test concentration
After abnormality collection, property data base is updated, then return step two carries out the computer room state of subsequent time
Judgement；
After step 11, property data base is updated, makes n=n+1, then computer room state of the return step two to subsequent time
Judged.
3. the method according to claim 1 or 2 using big data detection electric power computer room failure, which is characterized in that step
In three, detection collection and the similarity of state set in each control group are calculated method particularly includes:
The each element that will test concentration compares with each element in state set respectively and obtains the similarity between element
Value, using similarity value maximum between element as the similarity of detection collection and state set.
4. the method according to claim 3 using big data detection electric power computer room failure, which is characterized in that step 1
In, establish property data base method particularly includes:
The picture in computer room under various abnormalities in position to be judged is acquired in network large database concept, extracts the spy of each picture
It levies and using feature corresponding to same Exception Type state as an abnormality set, the abnormality of n type of acquisition
Set,
The picture in computer room under position normal condition to be judged is acquired in network large database concept, is acquired wait judge in computer room wait sentence
Picture under disconnected position normal condition, extracts the picture feature under each normal condition, as normal condition set,
Property data base is established using n abnormality set and normal condition set.
5. the method according to claim 4 using big data detection electric power computer room failure, which is characterized in that in step 1
After property data base is established, property data base is uploaded in block chain.
6. the method according to claim 5 using big data detection electric power computer room failure, which is characterized in that characteristic
After library updates, updated property data base is uploaded in block chain.
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Application publication date: 20190927 |