CN117013687A - Electric power operation quality monitoring method and system - Google Patents
Electric power operation quality monitoring method and system Download PDFInfo
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- 238000012544 monitoring process Methods 0.000 title claims abstract description 134
- 238000000034 method Methods 0.000 title claims abstract description 30
- 230000036541 health Effects 0.000 claims abstract description 31
- 238000012545 processing Methods 0.000 claims abstract description 24
- 238000004891 communication Methods 0.000 claims abstract description 6
- 230000008569 process Effects 0.000 claims description 13
- 238000012706 support-vector machine Methods 0.000 claims description 11
- 230000006870 function Effects 0.000 claims description 10
- 238000005265 energy consumption Methods 0.000 claims description 9
- 230000010485 coping Effects 0.000 claims description 8
- 238000000354 decomposition reaction Methods 0.000 claims description 7
- 230000002159 abnormal effect Effects 0.000 claims description 6
- 238000012790 confirmation Methods 0.000 claims description 6
- 230000005611 electricity Effects 0.000 claims description 6
- 230000007547 defect Effects 0.000 claims description 5
- 230000007613 environmental effect Effects 0.000 claims description 5
- 230000008859 change Effects 0.000 claims description 4
- 230000008439 repair process Effects 0.000 claims description 4
- 238000012216 screening Methods 0.000 claims description 2
- 230000005856 abnormality Effects 0.000 claims 1
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- 238000010586 diagram Methods 0.000 description 6
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- 238000004590 computer program Methods 0.000 description 4
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- 230000007774 longterm Effects 0.000 description 1
- 238000010801 machine learning Methods 0.000 description 1
Classifications
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00006—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00001—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by the display of information or by user interaction, e.g. supervisory control and data acquisition systems [SCADA] or graphical user interfaces [GUI]
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00002—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by monitoring
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Abstract
The invention provides a power operation quality monitoring method and a system, which relate to the technical field of power monitoring and comprise a monitoring platform, a database module, a plurality of monitoring sensors and a personnel management module, wherein the monitoring platform is in communication connection with the database module, the plurality of monitoring sensors and the personnel management module, the monitoring sensors acquire various state operation data of power equipment, the acquired operation data are uploaded to the monitoring platform, the monitoring platform analyzes and calculates the state operation data, determines health scores of each state operation data in the current operation state, determines whether the power equipment fails, and stores the data to the database module; the database module comprises a plurality of sub-databases, wherein the sub-databases are respectively provided with different numbers, and the databases with different numbers store state operation data uploaded by different monitoring sensors and fault processing schemes when the state operation data history has faults.
Description
Technical Field
The disclosure relates to the technical field of power monitoring, in particular to a power operation quality monitoring method and system.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
The power operation is based on a complex and unified structure of a power distribution network, the stability of the power operation is based on the safe stability of the operation of the power distribution network, the power grid refers to the whole formed by power transformation and distribution lines of various voltages in a power system, and is called as a power grid, and comprises three units of power transformation, power transmission and power distribution.
Electrical equipment is subjected to electrical, thermal, mechanical loading during operation, as well as the effects of natural environments such as high temperature, humidity, air pressure, etc., and may cause problems of aging, fatigue, and wear during long-term operation, resulting in poor operational stability. The fault and quality monitoring in the existing power equipment is generally concentrated on the equipment operation, the monitoring of operation data of the equipment is mainly aimed at, but the efficiency of monitoring the response of a terminal after the fault occurs is less than the improvement, after the equipment data is reminded of the fault, but due to the disorder of a duty system of a staff of the terminal, the fault data cannot be effectively monitored, the fault cannot be timely processed, the fault data of the equipment are often stored in a database, a large amount of time is required for calling different fault data, the data is compared in the database, the processing data of the corresponding fault cannot be effectively extracted, the repair of the fault is affected, and the safety and the stability of the power operation are affected.
Disclosure of Invention
In order to solve the problems, the disclosure provides a power operation quality monitoring method and a system, which are used for monitoring and displaying various data of power equipment, perfecting on-duty management of staff of a terminal, and simultaneously designing a corresponding storage database of various different data, so that the data of different faults can be stored in different databases, and timeliness of data retrieval and comparison is realized.
According to some embodiments, the present disclosure employs the following technical solutions:
the power operation quality monitoring system is characterized by comprising a monitoring platform, a database module, a plurality of monitoring sensors and a personnel management module, wherein the monitoring platform is in communication connection with the database module, the plurality of monitoring sensors and the personnel management module, the monitoring sensors acquire various state operation data of the power equipment, the acquired operation data are uploaded to the monitoring platform, the monitoring platform analyzes and calculates the state operation data, determines health scores of the fault state operation data in the current operation state, determines the severity of the fault of the power equipment, and stores all the data to the database module;
the method for acquiring the fault signal data of the state operation of the power equipment comprises the following steps: extracting characteristic quantity in the signal data, inputting the characteristic quantity into a support vector machine model for classification, calculating the shortest path length of the screened fault signal characteristic quantity and the reference characteristic quantity by using dynamic time warping, and then eliminating normal signals with wrong classification; performing health scoring on the classified fault signals, and analyzing the severity of the fault;
the database module comprises a plurality of sub-databases, wherein the sub-databases are respectively provided with different numbers, and the databases with different numbers store state operation data uploaded by different monitoring sensors and fault processing schemes when the state operation data history has faults.
According to some embodiments, the present disclosure employs the following technical solutions:
a power operation quality monitoring method, comprising:
monitoring the operation condition of the power equipment to obtain at least one state operation data of the power equipment;
uploading the acquired state operation data to a monitoring platform, and determining health scores of the power equipment in the current operation state according to preset scoring rules by the monitoring platform according to the state monitoring data corresponding to the power equipment;
and determining the operation health state of the power equipment, judging whether the power equipment fails, and uploading state operation data to a corresponding database for storage.
When judging that the state operation data of the power equipment is abnormal, acquiring a monitoring sensor for acquiring the state operation data, determining the number of the monitoring sensor, inquiring a database corresponding to the monitoring sensor, calling stored historical state operation data for comparison, and if the historical state operation data are consistent, repairing the power equipment by adopting a processing scheme under the historical fault;
if the state operation data are inconsistent, the state operation data are stored, a new coping process scheme is formulated, and the coping process scheme is stored.
Compared with the prior art, the beneficial effects of the present disclosure are:
the monitoring system aims at monitoring the operation data of the equipment, can improve the response efficiency of the monitoring terminal after the occurrence of the fault, and when the equipment data is reminded of the fault, the on-duty system of the staff of the monitoring terminal can effectively monitor the fault data, and the staff can timely process the fault after responsibility; corresponding storage databases are set according to different state operation data, when faults occur, the corresponding data storage databases can be found directly according to the sensors with corresponding numbers without comparison, and the safety and stability of the power system are effectively maintained.
Drawings
The accompanying drawings, which are included to provide a further understanding of the disclosure, illustrate and explain the exemplary embodiments of the disclosure and together with the description serve to explain the disclosure, and do not constitute an undue limitation on the disclosure.
FIG. 1 is a system architecture diagram of an embodiment of the present disclosure;
FIG. 2 is a flow chart of a method of storing fault operating state data of the present disclosure.
The specific embodiment is as follows:
the disclosure is further described below with reference to the drawings and examples.
It should be noted that the following detailed description is illustrative and is intended to provide further explanation of the present disclosure. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments in accordance with the present disclosure. As used herein, the singular is also intended to include the plural unless the context clearly indicates otherwise, and furthermore, it is to be understood that the terms "comprises" and/or "comprising" when used in this specification are taken to specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof.
Example 1
An embodiment of the disclosure provides an electric power operation quality monitoring system, which comprises a monitoring platform, a database module, a plurality of monitoring sensors and a personnel management module, wherein the monitoring platform is in communication connection with the database module, the plurality of monitoring sensors and the personnel management module, the monitoring sensors acquire various state operation data of electric power equipment, the acquired operation data are uploaded to the monitoring platform, the monitoring platform analyzes and calculates the state operation data, determines health scores of the fault state operation data in the current operation state, determines the severity of the fault of the electric power equipment, and stores all the data to the database module;
the method for acquiring the fault signal data of the state operation of the power equipment comprises the following steps: extracting characteristic quantity in the signal data, inputting the characteristic quantity into a support vector machine model for classification, calculating the shortest path length of the screened fault signal characteristic quantity and the reference characteristic quantity by using dynamic time warping, and then eliminating normal signals with wrong classification; performing health scoring on the classified fault signals, and analyzing the severity of the fault;
the database module comprises a plurality of sub-databases, wherein the sub-databases are respectively provided with different numbers, and the databases with different numbers store state operation data uploaded by different monitoring sensors and fault processing schemes when the state operation data history has faults.
As an embodiment, the monitoring platform establishes connection communication with the database module, the plurality of monitoring sensors and the personnel management module through a network, can collect and sort the running conditions of the power equipment in time according to the running conditions of the power equipment in time, and calculate the health score of the running of the power equipment after the running conditions are uploaded to the monitoring platform for state running data analysis, determine the severity of the failure of the power equipment and store all the data to the database module;
the database module comprises a plurality of sub-databases, wherein the sub-databases are respectively provided with different numbers, and the databases with different numbers store state operation data uploaded by different monitoring sensors and fault processing schemes when the state operation data history fails.
Specifically, the plurality of monitoring sensors are respectively used for acquiring different state operation data, and the state operation data comprises: equipment defect data, operating life data, dissolved gas content in oil data, environmental data, and energy consumption data.
The plurality of monitoring sensors are equipment defect data sensors, service life data sensors, dissolved gas content data sensors in oil, environment data sensors and energy consumption data sensors.
Wherein the environmental data includes: the energy consumption data are specific electricity consumption change conditions of the monitored power equipment, a graph can be generated according to the electricity consumption conditions, and the energy consumption change of the power equipment during electricity consumption can be judged.
And respectively numbering the plurality of monitoring sensors, and correspondingly numbering a plurality of sub-databases in the database module according to the monitoring sensors, namely respectively storing equipment defect data, operation age data, content data of dissolved gas in oil, environment data, energy consumption data and processing response schemes when historical faults occur in all different state data by the plurality of sub-databases.
Numbering a plurality of monitoring sensors, numbering the plurality of sub-databases in a one-to-one correspondence manner, and obtaining one or more state monitoring data, fault information under different state monitoring data and corresponding fault processing response schemes which are respectively stored in the sub-databases with different numbers in a corresponding manner. When the acquired state operation data in a certain monitoring sensor is abnormal, the historical fault data in the database corresponding to the serial number of the serial number monitoring sensor is preferentially called, comparison is carried out, and after the comparison is consistent, the historical fault processing scheme stored in the database carries out power equipment fault repair.
The personnel management module can realize the input, the check, the modification and the deletion of the data, if the data is input, the main interface of the monitoring platform is called, the formulated data newly added function is called, the corresponding database is called to inquire and judge whether the data is repeated, and if the data is repeated, the storage request is not sent to the database; if the data is not repeated, a storage request is sent to a database for storage.
The personnel management module comprises face recognition and an electronic signature, when a worker performs shift-over, the person on duty and the shift-over person fill in the electronic signature together, face recognition is performed, the shift-over person performs shift-over face confirmation, the person on duty performs off duty face confirmation, and meanwhile shift-over is completed, so that a certain monitoring person can be responsible in a system.
The personnel management module can display relevant basic information of the state operation data of the monitoring platform and can also check, modify and delete the state operation data. In the operation button column, the state operation data viewing can be entered by clicking the "view" button. The user can only modify the state operation data by only distributing the modification authority to the user without the authority, but only check the operation. Similarly, the user with authority can delete a certain piece of state operation data. Depending on the processing state of the state run data, the system will be divided into three states, "not started", "in progress" and "completed". The "not started" state refers to a list of state operation data compiling tasks issued by an upper department or the unit, the list records detailed information of the state operation data, and a lower unit or a team is required to complete the compiling of a system. An "in progress" state is when work is in progress with state-specific running data, which can be seen by the state. The 'completed' state refers to that state operation data is analyzed and stored within a specified time, and the state operation data can be released after the examination is completed by an upper department or a unit.
As an embodiment, when storing, determining the operation health status of the power equipment, judging whether a fault occurs, and uploading the status operation data to a corresponding database for storing. When judging that the state operation data of the power equipment is abnormal, acquiring a monitoring sensor for acquiring the state operation data, determining the number of the monitoring sensor, inquiring a database corresponding to the monitoring sensor, calling stored historical state operation data for comparison, and if the historical state operation data are consistent, repairing the power equipment by adopting a processing scheme under the historical fault;
if the state operation data are inconsistent, the state operation data are stored, a new coping process scheme is formulated, and the coping process scheme is stored.
Example 2
In one embodiment of the present disclosure, there is provided a power operation quality monitoring method including:
monitoring the operation condition of the power equipment to obtain at least one state operation data of the power equipment;
uploading the acquired state operation data to a monitoring platform, and determining health scores of the power equipment in the current operation state according to preset scoring rules by the monitoring platform according to the state monitoring data corresponding to the power equipment;
and determining the operation health state of the power equipment, judging whether the power equipment fails, and uploading state operation data to a corresponding database for storage.
As an embodiment, the specific implementation steps include:
establishing communication connection among a monitoring platform, the database module, various monitoring sensors and a personnel management module, acquiring various state operation data of the power equipment by the monitoring sensors, uploading the acquired operation data to the monitoring platform, analyzing and calculating the state operation data by the monitoring platform, determining health scores of each state operation data in the current operation state, determining whether the power equipment fails or not, and storing the data to the database module;
the database module comprises a plurality of sub-databases, wherein the sub-databases are respectively provided with different numbers, and the databases with different numbers store state operation data uploaded by different monitoring sensors and fault processing schemes when the state operation data history fails.
As one embodiment, the process of obtaining fault signal data for power device state operation includes: extracting characteristic quantity in the signal data, inputting the characteristic quantity into a support vector machine model for classification, calculating the shortest path length of the screened fault signal characteristic quantity and the reference characteristic quantity by using dynamic time warping, and then eliminating normal signals with wrong classification; performing health scoring on the classified fault signals, and analyzing the severity of the fault;
wherein, the step of rejecting the normal signal with wrong classification comprises the following steps: and carrying out wavelet packet decomposition on the obtained vibration signals operated in the operation state of the power equipment, calculating the energy entropy of the wavelet packets as characteristic values, classifying and screening fault signals by adopting a support vector machine to obtain vibration signals corresponding to the characteristic values, calculating the shortest path length between the characteristic values of the screened fault signals and the reference characteristic values by adopting a dynamic time regulation method, comparing the shortest path length with a threshold value, and eliminating normal signals misjudged by the support vector machine.
Specifically, performing wavelet packet decomposition on the obtained vibration signal, and calculating the energy entropy of the wavelet packet as a characteristic quantity;
the packet decomposition adopts db10 wavelet basis function to carry out 5-layer decomposition, and satisfies the following recurrence formula:
g in k＝ (-1) k h 1-k ，g k And h k The low-pass and high-pass filter coefficients, respectively, a sequence { u } constructed from the above equations n (x) "where n.epsilon.nn is the number of wavelet packet decomposition levels, where n=5 is taken to be called the basis functionAnd determining a wavelet packet.
Further, the energy entropy calculation process is as follows:
a. dividing the vibration signal x (t) and the like into N sections, and calculating to obtain:
wherein i=1, 2, …, N; t is t i-1 Is the starting point of the ith period of time; t is t i Is the i-th period end point.
b. Carrying out normalization processing on the calculated W (i), and calculating to obtain the W (i):
the energy entropy of the finally available vibration signal x (t) is:
taking n=5, and substituting the signals obtained by decomposing the wavelet packet into the above formula to obtain the energy entropy value of each component of the wavelet packet decomposition.
Further, a class of support vector machines adopts a specific class of machine learning method model to judge signals, and parameters of the class of support vector machines are set as follows: v=0.1, γ=1.
And calculating the shortest path length between the characteristic quantity of the screened fault signal and the reference characteristic quantity by adopting the existing time normalization function, comparing the shortest path length with a threshold value, and eliminating a class of normal signals which are misjudged by the support vector machine.
Specifically, the process of determining the health score of the fault state operation data in the current operation state is as follows:
determining a probability value of each state monitoring data of the power equipment in each health state according to a preset state membership function by using the score corresponding to each state monitoring data of the power equipment;
based on a D-S evidence theory, probability fusion is carried out according to probability values of each state monitoring data of the power equipment under each health state, so that probability fusion results corresponding to each health state of the power equipment are obtained; determining the running state of the power equipment according to probability fusion results corresponding to each health state of the power equipment;
and carrying out zero removal processing on the obtained probability value of each state monitoring data of the power equipment under each health state so as to prevent Zadeh paradox.
Probability fusion is carried out according to probability values of each state monitoring data of the power equipment under each health state to obtain probability fusion results corresponding to each health state, and the probability fusion results comprise:
wherein, S Ai is the probability fusion result when the health state is Ai; p m (Ai) is the probability value of the mth item of state monitoring data when the health state is Ai; n is the total number of health states; m is the total quantity of the state monitoring data.
And selecting the health state corresponding to the maximum value in the probability fusion results corresponding to each health state of the power equipment as the running state of the power equipment.
As an embodiment, the method for judging the power equipment fault is as follows:
monitoring the operation condition of the power equipment to obtain at least one state operation data of the power equipment;
uploading the acquired state operation data to a monitoring platform, and determining health scores of the power equipment in a fault operation state according to preset scoring rules by the monitoring platform according to the state monitoring data corresponding to the power equipment;
determining the operation health state of the power equipment, judging the severity of the fault, and uploading state operation data to a corresponding database for storage; when judging that the state operation data of the power equipment is abnormal, acquiring a monitoring sensor for acquiring the state operation data, determining the number of the monitoring sensor, inquiring a database corresponding to the monitoring sensor, calling stored historical state operation data for comparison, and if the historical state operation data are consistent, repairing the power equipment by adopting a processing scheme under the historical fault;
if the state operation data are inconsistent, the state operation data are stored, a new coping process scheme is formulated, and the coping process scheme is stored.
Numbering a plurality of monitoring sensors, numbering the plurality of sub-databases in a one-to-one correspondence manner, and obtaining one or more state monitoring data, fault information under different state monitoring data and corresponding fault processing response schemes which are respectively stored in the sub-databases with different numbers in a corresponding manner. When the acquired state operation data in a certain monitoring sensor is abnormal, the historical fault data in the database corresponding to the serial number of the serial number monitoring sensor is preferentially called, comparison is carried out, and after the comparison is consistent, the historical fault processing scheme stored in the database carries out power equipment fault repair.
As one embodiment, the method for storing fault state operation data is as follows:
and acquiring certain fault state operation data, determining the number of a monitoring sensor for acquiring the state operation data, determining the number of a sub-database corresponding to the monitoring sensor, comparing the state operation data with historical data in the sub-database, if the comparison is consistent, not storing, and if the comparison is different, storing.
As an embodiment, the management manner of the personnel management module includes:
the personnel management module comprises face recognition and an electronic signature, when a worker performs shift-over, the person on duty and the shift-over person fill in the electronic signature together, face recognition is performed, the shift-over person performs shift-over face confirmation, the person on duty performs off duty face confirmation, meanwhile, shift-over is completed, and the system can be responsible for a certain monitoring person.
In the personnel management module, a patrol function is further set, and in order to ensure the convenience and accuracy of information input of patrol personnel, the personnel management module designs a batch import function. The patrol personnel can input a plurality of pieces of patrol data into the Excel preferentially, and the batch importing function in the personnel management module is used, so that the batch importing of a plurality of pieces of data can be realized, and a lot of time is saved. Similarly, the inspection data is also equipment-specific information, the correctness and the uniqueness of the data must be ensured, and in order to distinguish the time difference, a date label is specially formulated to show the difference when the personnel management module is implemented. In the inspection task list, each inspection task mainly comprises a task inspection name, a device type, a work responsible person, a work class member, a class auditing state, a unit lead auditing state, a task making date, a task execution date and the like, and the information can be checked by a user, but if modification and deletion operations are required, permission of a task authority manager must be acquired. Similarly, "not started", "in progress" and "completed" correspond to the patrol task, respectively.
The present disclosure is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the disclosure. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While the specific embodiments of the present disclosure have been described above with reference to the drawings, it should be understood that the present disclosure is not limited to the embodiments, and that various modifications and changes can be made by one skilled in the art without inventive effort on the basis of the technical solutions of the present disclosure while remaining within the scope of the present disclosure.
Claims (10)
1. The power operation quality monitoring system is characterized by comprising a monitoring platform, a database module, a plurality of monitoring sensors and a personnel management module, wherein the monitoring platform is in communication connection with the database module, the plurality of monitoring sensors and the personnel management module, the monitoring sensors acquire various state operation data of the power equipment, the acquired operation data are uploaded to the monitoring platform, the monitoring platform analyzes and calculates the state operation data, determines health scores of the fault state operation data in the current operation state, determines the severity of the fault of the power equipment, and stores all the data to the database module;
the method for acquiring the fault signal data of the state operation of the power equipment comprises the following steps: extracting characteristic quantity in the signal data, inputting the characteristic quantity into a support vector machine model for classification, calculating the shortest path length of the screened fault signal characteristic quantity and the reference characteristic quantity by using dynamic time warping, and then eliminating normal signals with wrong classification; performing health scoring on the classified fault signals, and analyzing the severity of the fault;
the database module comprises a plurality of sub-databases, wherein the sub-databases are respectively provided with different numbers, and the databases with different numbers store state operation data uploaded by different monitoring sensors and fault processing schemes when the state operation data history has faults.
2. The power operation quality monitoring system according to claim 1, wherein the plurality of monitoring sensors are respectively used to acquire different state operation data, the state operation data including: equipment defect data, operating life data, dissolved gas content in oil data, environmental data, and energy consumption data.
3. A power operation quality monitoring system according to claim 2 wherein said environmental data comprises: the energy consumption data are specific electricity consumption change conditions of the monitored power equipment, a graph is generated according to the electricity consumption conditions, and the energy consumption change of the power equipment during electricity consumption is judged.
4. An electric power operation quality monitoring system according to claim 1, wherein the database module comprises a plurality of sub-databases for storing equipment defect data, operational age data, dissolved gas content data in oil, environmental data and energy consumption data, and processing solutions when a history fault occurs in all different state data, respectively.
5. The power operation quality monitoring system according to claim 4, wherein a plurality of monitoring sensors are numbered and the plurality of sub-databases are numbered in one-to-one correspondence, and one or more status monitoring data, fault information under different status monitoring data and corresponding fault handling schemes are acquired and stored in the sub-databases of different numbers in correspondence, respectively.
6. The power operation quality monitoring system according to claim 5, wherein when abnormality occurs in the state operation data in one of the obtained monitoring sensors, the historical fault data in the database of the number corresponding to the number monitoring sensor is preferentially retrieved, and compared, and after the comparison is consistent, the historical fault processing scheme stored in the database performs power equipment fault repair.
7. The power operation quality monitoring system according to claim 1, wherein the personnel management module is capable of realizing data entry, checking, modifying and deleting, if the data is entered, calling a formulated data newly-added function on a monitoring platform main interface, calling a corresponding database to inquire and judge whether the data is repeated, and if the data is repeated, not sending a storage request to the database; if the data is not repeated, a storage request is sent to a database for storage.
8. The power operation quality monitoring system according to claim 7, wherein the personnel management module includes face recognition and electronic signature, when the staff performs the shift, the person on duty and the shift person fill in the determined electronic signature together, and perform face recognition, the shift person performs shift face confirmation, the person on duty performs shift face confirmation, and at the same time, the shift is completed, and the system can be responsible for a certain monitoring person.
9. A power operation quality monitoring system according to claim 1, wherein said step of rejecting a normal signal for classification errors comprises: and carrying out wavelet packet decomposition on the obtained vibration signals operated in the operation state of the power equipment, calculating the energy entropy of the wavelet packets as characteristic values, classifying and screening fault signals by adopting a support vector machine to obtain vibration signals corresponding to the characteristic values, calculating the shortest path length between the characteristic values of the screened fault signals and the reference characteristic values by adopting a dynamic time regulation method, comparing the shortest path length with a threshold value, and eliminating normal signals misjudged by the support vector machine.
10. A method for monitoring the quality of electric power operation, comprising:
monitoring the operation condition of the power equipment to obtain at least one state operation data of the power equipment;
uploading the acquired state operation data to a monitoring platform, and determining health scores of the power equipment in a fault operation state according to preset scoring rules by the monitoring platform according to the state monitoring data corresponding to the power equipment;
determining the operation health state of the power equipment, judging the severity of the fault, and uploading state operation data to a corresponding database for storage; when judging that the state operation data of the power equipment is abnormal, acquiring a monitoring sensor for acquiring the state operation data, determining the number of the monitoring sensor, inquiring a database corresponding to the monitoring sensor, calling stored historical state operation data for comparison, and if the historical state operation data are consistent, repairing the power equipment by adopting a processing scheme under the historical fault;
if the state operation data are inconsistent, the state operation data are stored, a new coping process scheme is formulated, and the coping process scheme is stored.
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| CN202310736426.2A CN117013687A (en) | 2023-06-20 | 2023-06-20 | Electric power operation quality monitoring method and system |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117236805A (en) * | 2023-11-16 | 2023-12-15 | 北京国电通网络技术有限公司 | Power equipment control method, device, electronic equipment and computer readable medium |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117236805A (en) * | 2023-11-16 | 2023-12-15 | 北京国电通网络技术有限公司 | Power equipment control method, device, electronic equipment and computer readable medium |
| CN117236805B (en) * | 2023-11-16 | 2024-02-02 | 北京国电通网络技术有限公司 | Power equipment control method, device, electronic equipment and computer readable medium |
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