CN110347717A - A kind of big data storage method based on urban electric power equipment monitoring - Google Patents
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Abstract
The present invention relates to power equipment monitoring technical fields, and disclose a kind of big data storage method based on urban electric power equipment monitoring, comprising the following steps: step 1: acquiring urban electric power related data and establishing indagation identification library, extract signal and characteristic parameter etc..Step 2: selecting look-ahead and overlap operation technology, operation.Step 3: choosing suitable training set and test set in the data of acquisition early period.Step 4: inquiring corresponding historical data from cloud database, compared using statistical analysis algorithms and using normal distribution.The big data storage method based on urban electric power equipment monitoring, using cloud computing technology, it is compared and analyzed using statistical analysis algorithms and using normal distribution, data memory convenient for starting to write to electric power collects real-time monitoring, technical support is provided for electrical equipment online supervision, the reliability for improving Distribution Network Equipment power supply simultaneously, has ensured that power grid can be safe, stable operation.
Description
Technical field
The present invention relates to power equipment monitoring technical field, specially a kind of big data based on urban electric power equipment monitoring
Storage method.
Background technique
Electrical Equipment On-Line Monitoring System is by temperature on-line monitoring device, lightning arrester insulation on-Line Monitor Device, breaker
On-Line Monitor Device composition, system cover the monitoring of substation's electric equipments state of insulation parameter, and monitoring parameter is more, function
It can be complete.System can also be made of with flexible configuration therein a set of or two covering devices, also optional when necessary to match transformer oil colours
Compose monitoring device.
Big data is commonly referred to as those enormous amounts, is difficult to the data set collected, handle and analyzed, and also refers to those and is passing
The data saved for a long time in system infrastructure.Big data storage is that these data sets are persisted in computer, and big data is answered
One is mainly characterized by real-time or near real-time, and explosive with big data application increases, it has been derived
Oneself unique framework, and pushed directly on the development of storage, network and computing technique.
Existing electric power data storage method can only gradually combine inspection to run unit on grid equipment monitoring problem
Carry out status monitoring, can not really and normally carry out on-line monitoring, and existing electric power data storage method can not be in failure
Before, corresponding early warning and prompt are made, failure scene and reason cannot be prejudged in time, cannot ensure power grid security and stabilization
Operation, thus it is proposed that a kind of big data storage method based on urban electric power equipment monitoring.
Summary of the invention
The present invention provides a kind of big data storage method based on urban electric power equipment monitoring, has and ensure that power grid can
The advantages of safety, stable operation is with carrying out early warning in time, improving apparatus of electrical monitoring equipment prevention effect, solves background technique
In the problem of mentioning.
Be achieved in order to achieve the above object, the present invention provides the following technical solutions: one kind is based on urban electric power Supervision
The big data storage method of survey, comprising the following steps:
Step 1: acquiring urban electric power related data and establishing indagation identification library, signal and characteristic parameter etc. are extracted.
Step 2: selecting look-ahead and overlap operation technology, operation.
Step 3: choosing suitable training set and test set in the data of acquisition early period.
Step 4: corresponding historical data is inquired from cloud database, using statistical analysis algorithms and using normal state point
Butut compares, normal distribution i.e. due to general normal population, its image is not necessarily symmetrical about y-axis, for it is any just
State is overall, and value is less than the probability of x, as long as can ask normal population in the probability of some specific sections with it, in order to just
In description and application, normal variate is often made into data conversion, the standards such as the partial discharge state separation and related valves of assessment equipment are straight
Parameter.
Step 5: the data to modeling diagnose, analyzed using diagnosis algorithms such as vector machine, data models, it is right
Monitoring data carry out class when reasoning with the experience accumulated in the past, and ultrasonic wave local discharge detection device is equipped with data storage function
Can, ultrasonic wave shelf depreciation live detection detected before preparation, test point select, background detection, signal general survey, just
Step positioning, signal close mapping, signal make a definite diagnosis with multiple links such as analysis report, before detection starts, by background and test point
The measurement of ultrasonic signal virtual value, amplitude, frequency dependence, phase and original waveform judges whether normally, if there is exception
Signal, is just further analyzed to identify equipment detected with the presence or absence of obvious shortcoming, the reason of to determine defect and position；For
Those suspected defects, some intermittent and unstable abnormal signals can use other different detection means such as superfrequencies, infrared survey
Temperature, decomposition product analysis, X-ray etc. carry out auxiliary detection.
Testing staff can also by being smoothly placed on hand-held ultrasound wave sensor on each test point of device housings,
After signal stabilization, observation signal situation 10 seconds or more time will avoid the shake of sensor in detection, and avoid tester's
Clothing, signal cable and other objects are contacted or are rubbed with the shell of power equipment to be measured, detection ambient noise signal and
When suspicious abnormal signal, then convenient for being stored to data, to compare and to analyze.
Step 6: obtaining correct diagnosis, has the characteristics that stronger directionality by ultrasonic signal propagation, therefore
Ultrasonic wave Partial Discharge Detection is widely used in the accurate positioning of defect, and then object positions the position of fault, is convenient for
Staff checks, and ultrasonic wave local discharge detection device mainly joins the identification of defect type according to leather testing staff to detection
Number is judged after being analyzed, and when failure does not occur, makes early warning time of failure, place and event of failure.
Optionally, in second step, assembly line is calculated and analyzed in real time to the electric apparatus monitoring data of Computational frame, is handed over
It pitches the disaggregated models such as the parallel storage of access and carries out identification ultrasonic wave shelf depreciation, shelf depreciation letter is generated inside power equipment
Number when, vibration and the sound of impact can be generated, and data are uploaded into cloud, pass through and ultrasound is installed on not standby chamber outer wall
The characteristics of wave sensor measures local discharge signal, this method is the electric loop of sensor and power equipment without any
System, not by the interference of electrical aspect.
Optionally, in the third step, it is modeled using different kernel functions and parameter combined training collection, selects choosing and closes
Suitable modeling scheme.
Optionally, steps are as follows for the choosing of selecting of the suitable modeling scheme, utilizes test set to the various models built up
It is tested, the superiority and inferiority of more each kernel function, selects optimum function model, realize the identification of infrared measurement of temperature intelligent pattern and answered
With.
Optionally, the cloud database capital equipment include cloud computing server, disk array, internet exchange system and
Associated safety access device.
Optionally, indagation identification library initially sets up data mining library, carries out Data Stream Processing later, and data flow can be with
It is indicated with the data flow diagram that the directed arc by node and connecting node forms, the operation or function that node on behalf executes are oriented
Arc represents the order that node is performed, in general, data flow architecture is described with a five-tuple, finally to data Classification and Identification.
The present invention provides a kind of big data storage methods based on urban electric power equipment monitoring, have following beneficial to effect
Fruit:
1, it is somebody's turn to do the big data storage method based on urban electric power equipment monitoring and statistical analysis is utilized using cloud computing technology
Algorithm is simultaneously compared and analyzed using normal distribution, and the data memory convenient for starting to write to electric power collects real-time monitoring, is electric power
Equipment on-line monitoring provides technical support, while improving the reliability of Distribution Network Equipment power supply, has ensured that power grid can be safe,
Stable operation.
2, it is somebody's turn to do the big data storage method based on urban electric power equipment monitoring, the diagnosis such as vector machine, data model is utilized to calculate
Method is analyzed, and with the experience accumulated in the past look into monitoring data suitable, is assessed convenient for the operating state to power grid, just
In pending before death in failure, early warning is carried out in time, improves the prevention effect of apparatus of electrical monitoring equipment.
Detailed description of the invention
Fig. 1 is overall procedure schematic diagram of the invention；
Fig. 2 is cloud database major device class schematic diagram in Fig. 1；
Fig. 3 is the step flow diagram that modeling scheme selects choosing in Fig. 1；
Fig. 4 is the step flow diagram that indagation identifies library in Fig. 1.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other
Embodiment shall fall within the protection scope of the present invention.
Please refer to Fig. 1-4, a kind of big data storage method based on urban electric power equipment monitoring, comprising the following steps:
Step 1: acquiring urban electric power related data and establishing indagation identification library, signal and characteristic parameter etc. are extracted.
Step 2: selecting look-ahead and overlap operation technology, operation.
Step 3: choosing suitable training set and test set in the data of acquisition early period.
Step 4: corresponding historical data is inquired from cloud database, using statistical analysis algorithms and using normal state point
Butut compares, normal distribution i.e. due to general normal population, its image is not necessarily symmetrical about y-axis, for it is any just
State is overall, and value is less than the probability of x.As long as can ask normal population in the probability of some specific sections with it, in order to just
In description and application, normal variate is often made into data conversion, general normal distribution is converted to standardized normal distribution assessment equipment
Partial discharge state separation and the standard parameters such as related valves are straight.
Step 5: the data to modeling diagnose, analyzed using diagnosis algorithms such as vector machine, data models, it is right
Monitoring data carry out class when reasoning with the experience accumulated in the past, and ultrasonic wave local discharge detection device is equipped with data storage function
Can, when detecting ambient noise signal and suspicious abnormal signal, then convenient for being stored to data, to compare
And analysis.
Step 6: obtain correct diagnosis, when failure does not occur, make early warning time of failure, place and
Event of failure, ultrasonic wave Partial Discharge Detection to the defects of particle, suspended discharge, point discharge, loosening, foreign matter impurity have compared with
Good detection effect, while being to complement one another and verify by ultrasonic wave Partial Discharge Detection and superfrequency Partial Discharge Detection.
Wherein, in second step, assembly line is calculated and analyzed in real time to the electric apparatus monitoring data of Computational frame, is intersected
The disaggregated models such as the parallel storage of access carry out identification ultrasonic wave shelf depreciation, generate local discharge signal inside power equipment
When, vibration and the sound of impact can be generated, and data are uploaded into cloud, by installing ultrasonic wave on not standby chamber outer wall
The characteristics of sensor measures local discharge signal, this method is that the electric loop of sensor and power equipment is contacted without any,
Not by the interference of electrical aspect.
Wherein, in the third step, it is modeled using different kernel functions and parameter combined training collection, it is suitable selects choosing
Modeling scheme.
Wherein, steps are as follows for the choosing of selecting of suitable modeling scheme, is surveyed to the various models built up using test set
Examination, the superiority and inferiority of more each kernel function select optimum function model, realize the identification of infrared measurement of temperature intelligent pattern and application.
Wherein, cloud database capital equipment includes cloud computing server, disk array, internet exchange system and related peace
Full access device.
Wherein, indagation identification library initially sets up data mining library, carries out Data Stream Processing later, data flow can be with by saving
The data flow diagram that point and the directed arc of connecting node form indicates that the operation or function that node on behalf executes, directed arc represent
The order that node is performed, in general, data flow architecture is described with a five-tuple, finally to data Classification and Identification.
It should be noted that, in this document, relational terms such as first and second and the like are used merely to a reality
Body or operation are distinguished with another entity or operation, are deposited without necessarily requiring or implying between these entities or operation
In any actual relationship or order or sequence.Moreover, the terms "include", "comprise" or its any other variant are intended to
Non-exclusive inclusion, so that the process, method, article or equipment including a series of elements is not only wanted including those
Element, but also including other elements that are not explicitly listed, or further include for this process, method, article or equipment
Intrinsic element.
It although an embodiment of the present invention has been shown and described, for the ordinary skill in the art, can be with
A variety of variations, modification, replacement can be carried out to these embodiments without departing from the principles and spirit of the present invention by understanding
And modification, the scope of the present invention is defined by the appended.
Claims (6)
1. a kind of big data storage method based on urban electric power equipment monitoring, it is characterised in that: the following steps are included:
Step 1: acquiring urban electric power related data and establishing indagation identification library, signal and characteristic parameter etc. are extracted.
Step 2: selecting look-ahead and overlap operation technology, operation.
Step 3: choosing suitable training set and test set in the data of acquisition early period.
Step 4: inquiring corresponding historical data from cloud database, using statistical analysis algorithms and normal distribution is used
It compares, the standard parameters such as the partial discharge state separation and related valves of assessment equipment are straight.
Step 5: the data to modeling diagnose, analyzed using diagnosis algorithms such as vector machine, data models, to monitoring
Data carry out class when reasoning with the experience accumulated in the past.
Step 6: obtaining correct diagnosis, when failure does not occur, early warning time of failure, place and failure are made
Event.
2. a kind of big data storage method based on urban electric power equipment monitoring according to claim 1, it is characterised in that:
In second step, assembly line is calculated and analyzes in real time to the electric apparatus monitoring data of Computational frame, the parallel of interleaving access is deposited
The disaggregated models such as reservoir carry out identification ultrasonic wave shelf depreciation, and data are uploaded cloud.
3. a kind of big data storage method based on urban electric power equipment monitoring according to claim 1, it is characterised in that:
In the third step, it is modeled using different kernel functions and parameter combined training collection, selects and selects suitable modeling scheme.
4. a kind of big data storage method based on urban electric power equipment monitoring according to claim 3, it is characterised in that:
Steps are as follows for the choosing of selecting of the suitable modeling scheme, is tested using test set the various models built up, relatively more each
The superiority and inferiority of kernel function selects optimum function model, realizes the identification of infrared measurement of temperature intelligent pattern and application.
5. a kind of big data storage method based on urban electric power equipment monitoring according to claim 1, it is characterised in that:
The cloud database capital equipment includes that cloud computing server, disk array, internet exchange system and associated safety access are set
It is standby.
6. a kind of big data storage method based on urban electric power equipment monitoring according to claim 1, it is characterised in that:
Indagation identification library initially sets up data mining library, Data Stream Processing is carried out later, finally to data Classification and Identification.
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| CN111324460A (en) * | 2020-02-19 | 2020-06-23 | 云南电网有限责任公司 | Power monitoring control system and method based on cloud computing platform |
| CN112269821A (en) * | 2020-10-30 | 2021-01-26 | 内蒙古电力(集团)有限责任公司乌海超高压供电局 | Power equipment state analysis method based on big data |
| CN112562698A (en) * | 2020-12-02 | 2021-03-26 | 国网山西省电力公司大同供电公司 | Power equipment defect diagnosis method based on fusion of sound source information and thermal imaging characteristics |
| CN112580993A (en) * | 2020-12-23 | 2021-03-30 | 云南电网有限责任公司昆明供电局 | Power grid equipment fault probability analysis method |
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