CN116951330A - Large transformer online live oil filtering pipeline leakage detection method - Google Patents
Large transformer online live oil filtering pipeline leakage detection method Download PDFInfo
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- CN116951330A CN116951330A CN202310949203.4A CN202310949203A CN116951330A CN 116951330 A CN116951330 A CN 116951330A CN 202310949203 A CN202310949203 A CN 202310949203A CN 116951330 A CN116951330 A CN 116951330A
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- 238000001914 filtration Methods 0.000 title claims abstract description 60
- 238000001514 detection method Methods 0.000 title claims abstract description 29
- 239000007788 liquid Substances 0.000 claims abstract description 40
- 238000012544 monitoring process Methods 0.000 claims abstract description 32
- 238000000034 method Methods 0.000 claims abstract description 20
- 238000013500 data storage Methods 0.000 claims abstract description 11
- 238000007689 inspection Methods 0.000 claims abstract description 6
- 230000008859 change Effects 0.000 claims description 24
- 238000007726 management method Methods 0.000 claims description 20
- 238000013499 data model Methods 0.000 claims description 11
- 230000005540 biological transmission Effects 0.000 claims description 7
- 230000000007 visual effect Effects 0.000 claims description 4
- 230000003442 weekly effect Effects 0.000 claims description 4
- 239000003623 enhancer Substances 0.000 claims description 3
- 238000004364 calculation method Methods 0.000 abstract description 3
- 230000007613 environmental effect Effects 0.000 abstract description 3
- 230000009286 beneficial effect Effects 0.000 abstract description 2
- 238000012423 maintenance Methods 0.000 abstract 1
- 239000012530 fluid Substances 0.000 description 4
- 239000000126 substance Substances 0.000 description 3
- 230000002159 abnormal effect Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000009413 insulation Methods 0.000 description 1
- 210000001503 joint Anatomy 0.000 description 1
- 239000002923 metal particle Substances 0.000 description 1
- -1 oxides Substances 0.000 description 1
- 239000002245 particle Substances 0.000 description 1
- 238000000746 purification Methods 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
Classifications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D21/00—Measuring or testing not otherwise provided for
- G01D21/02—Measuring two or more variables by means not covered by a single other subclass
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F17—STORING OR DISTRIBUTING GASES OR LIQUIDS
- F17D—PIPE-LINE SYSTEMS; PIPE-LINES
- F17D5/00—Protection or supervision of installations
- F17D5/02—Preventing, monitoring, or locating loss
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F17—STORING OR DISTRIBUTING GASES OR LIQUIDS
- F17D—PIPE-LINE SYSTEMS; PIPE-LINES
- F17D5/00—Protection or supervision of installations
- F17D5/02—Preventing, monitoring, or locating loss
- F17D5/06—Preventing, monitoring, or locating loss using electric or acoustic means
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- Engineering & Computer Science (AREA)
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- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Acoustics & Sound (AREA)
- Examining Or Testing Airtightness (AREA)
Abstract
The invention discloses a large transformer online live oil filtering pipeline leakage detection method, which comprises the following steps: s1: inspection maintenance, S2: setting a reference, and S3: flow monitoring, S4: temperature monitoring, S5: voltage monitoring, S6: liquid level monitoring, S7: data enhancement, S8: data statistics, S9: data storage, S10: chart comparison, S11: an alarm is issued. The beneficial effects of the invention are as follows: by carrying out automatic comparison calculation on each monitoring data, judging whether oil leakage exists in oil treatment systems such as an oil filter and the like, and automatically commanding and controlling the correct operation of the systems; the method has the advantages that a large amount of transformer oil leakage is avoided, serious environmental and safety accidents are caused, target data can be quickly searched through a unified database, and the leakage position of the pipeline can be quickly found by calling historical data in the database for comparison, so that the method has the function of quickly positioning and leak detection when the online live oil filtering pipeline leakage detection method of the large transformer is used.
Description
Technical Field
The invention relates to the technical field of pipeline leakage detection methods, in particular to an online live oil filtering pipeline leakage detection method for a large transformer.
Background
The online live oil filtering of the large transformer is characterized in that the transformer is subjected to purification treatment under the operation state, moisture, gas, solid particles, oxides, metal particles and the like in the transformer oil are required to be removed, insulation performance indexes of the transformer insulating oil are guaranteed, and safety indexes such as stability and reliability of the operation of an oil filtering process system are required to be guaranteed.
However, online oil filtering has the defect of difficult transformer oil leakage monitoring, the transformer can cause too high working temperature due to factors such as short circuit and overload, the oil temperature rises, oil leakage is easy to occur, the reasons for oil leakage include that a sleeve pipe is not matched with a conducting rod or a gasket is not tightly sealed, a pipeline oil drain valve is loose, a pipeline connecting part is not fit enough, and then the oil filtering pipeline is leaked, and leakage and oil seepage of the oil filtering pipeline usually occur at each connecting part of the transformer.
Disclosure of Invention
The invention aims to provide a large-scale transformer online live oil filter pipeline leakage detection method, which aims to solve the problems that when the large-scale transformer online live oil filter pipeline leakage detection method provided by the background art is used, slight oil leakage is difficult to discover in time, and only if the pipeline leakage reaches a certain degree, the pipeline leakage can be discovered by inspection staff or monitoring equipment, so that the use requirements of people cannot be met.
In order to achieve the above purpose, the present invention provides the following technical solutions: a large transformer online live oil filtering pipeline leakage detection method comprises the following steps:
s1: checking and maintaining, namely checking and maintaining the electrified oil filtering pipeline through regular inspection of staff;
s2: setting a reference, and setting a threshold value of detection equipment according to the actual condition of the electrified oil filtering pipeline;
s3: flow monitoring, namely detecting inflow and outflow of liquid in the electrified oil filtering pipeline, judging whether the flow deviation rate exceeds a preset threshold value, and displaying prompt information if the flow deviation rate exceeds the preset threshold value;
s4: temperature monitoring, namely detecting temperature change in the electrified oil filtering pipeline, judging whether the temperature deviation exceeds a preset threshold value, and displaying prompt information if the temperature deviation exceeds the preset threshold value;
s5: voltage monitoring, namely detecting voltage change of the electrified oil filtering pipeline, judging whether the voltage deviation exceeds a preset threshold value, and displaying prompt information if the voltage deviation exceeds the preset threshold value;
s6: monitoring the liquid level, detecting the liquid level change in the oil drain tank, judging whether the liquid in the oil drain tank exceeds a preset threshold value, and displaying prompt information if the liquid exceeds the preset threshold value;
s7: data enhancement, namely reducing transmission pressure of detection information of the electrified oil filtering pipeline;
s8: data statistics is carried out according to a preset standard, and a map and a table are formed;
s9: data storage, namely importing the counted atlas and table into a database for storage;
s10: comparing the graphs, firstly calling the past date data in the database to make a data model, and then comparing the data model with the current graphs and tables in real time;
s11: and sending out an alarm, and immediately sending out an alarm notification to the management platform and the mobile terminal when the live oil filtering pipe is found out to be leaked by online real-time comparison.
Preferably, in the step S3, the mass-volume balance method is used in combination with the ultrasonic flowmeter to monitor the inflow and outflow of the liquid in the live oil filter pipeline, and when the difference in the live oil filter pipeline is greater than a certain range, the detected pipeline is indicated to be likely to leak, and the information of monitoring the leakage of the pipeline is transmitted through a wireless network.
Preferably, in step S4, the temperature change in the live oil filter pipeline is monitored by a pipeline temperature monitor, and the error is reduced by detecting the temperature at multiple points in a designated area.
Preferably, in step S5, the voltage monitor monitors the voltage change in the live oil filter pipeline, and the voltage monitor is further connected with the live oil filter pipeline through a wire and a sensor, when the live oil filter pipeline leaks, the voltage monitor, the wire, the sensor and the live oil filter pipeline are connected to form a new loop, so that the live oil filter pipeline is found to leak.
Preferably, in step S6, the liquid level monitor continuously sends out ultrasonic waves to detect the liquid level change in the oil drain tank, and the ultrasonic waves are reflected by contacting with the liquid in the oil drain tank, so as to obtain the liquid level change in the oil drain tank.
Preferably, in step S7, the transmission speed of the wireless network is increased by the wireless network signal enhancer.
Preferably, in the step S8, the data statistics is performed according to unit information management, user information management, and authority information management, so as to form a daily chart, a weekly chart, a monthly chart, a quarterly chart, and a yearly chart.
Preferably, in step S9, the data storage is performed by a storage server, and the server is a permanent server, so as to prevent data loss.
Preferably, in step S10, the database is accessed remotely, so as to realize real-time data calling, and the called data model requires a special key for unlocking the encrypted data.
Preferably, in step S11, when the leakage of the live oil filter pipeline is found, the audible and visual alarm is used to make sound and flash, so as to remind the field staff of the leakage of the pipeline.
Compared with the prior art, the invention has the beneficial effects that: by carrying out automatic comparison calculation on each monitoring data, judging whether oil leakage exists in oil treatment systems such as an oil filter and the like, and automatically commanding and controlling the correct operation of the systems; the method has the advantages that a large amount of transformer oil leakage is avoided, serious environmental and safety accidents are caused, target data can be quickly searched through a unified database, and the leakage position of the pipeline can be quickly found by calling historical data in the database for comparison, so that the method has the function of quickly positioning and leak detection when the online live oil filtering pipeline leakage detection method of the large transformer is used.
Drawings
FIG. 1 is a schematic flow diagram of a large-scale transformer on-line live oil filter pipeline leakage detection method.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, the present invention provides a technical solution: a large transformer online live oil filtering pipeline leakage detection method comprises the following steps:
s1: checking and maintaining, namely checking and maintaining the electrified oil filtering pipeline through regular inspection of staff; the ultrasonic flowmeter, the pipeline temperature monitor, the voltage monitor, the liquid level monitor and other monitoring equipment are inspected together during the inspection of the staff, so that the liquid level monitor is prevented from malfunctioning;
s2: setting a reference, and setting a threshold value of detection equipment according to the actual condition of the electrified oil filtering pipeline; when the threshold value of the detection equipment is set, the threshold values of monitoring equipment such as an ultrasonic flowmeter, a pipeline temperature monitor, a voltage monitor and a liquid level monitor are set through the threshold values sent by the database;
s3: flow monitoring, namely detecting inflow and outflow of liquid in the electrified oil filtering pipeline, judging whether the flow deviation rate exceeds a preset threshold value, and displaying prompt information if the flow deviation rate exceeds the preset threshold value; monitoring inflow and outflow of liquid in the charged oil filtering pipeline by a mass-volume balance method in combination with an ultrasonic flowmeter, and transmitting information of the leakage of the monitored pipeline through a wireless network when the difference value in the charged oil filtering pipeline is larger than a certain range; the mass-volume balance method is based on the mass or volume conservation relation of the fluid substance flowing in the pipeline, namely the difference between the inflow and outflow of the liquid is equal to the stagnant fluid quantity in the pipeline; after the pipeline operation is stable, the inflow and outflow are regarded as equal, and then ultrasonic flow meters are arranged on the electrified oil filtering pipeline at equal intervals, so that the input and output flow rates of multiple points of the ultrasonic flow meters are detected;
s4: temperature monitoring, namely detecting temperature change in the electrified oil filtering pipeline, judging whether the temperature deviation exceeds a preset threshold value, and displaying prompt information if the temperature deviation exceeds the preset threshold value; monitoring the temperature change in the electrified oil filtering pipeline through a pipeline temperature monitor, and reducing errors through multipoint temperature detection in a designated area; the interior of the pipeline temperature monitor is connected with a microprocessor in a butt joint way, and the microprocessor integrates the monitored actual temperature values to form a map and then sends the map;
s5: voltage monitoring, namely detecting voltage change of the electrified oil filtering pipeline, judging whether the voltage deviation exceeds a preset threshold value, and displaying prompt information if the voltage deviation exceeds the preset threshold value; the voltage monitor monitors the voltage change in the live oil filtering pipeline, the voltage monitor is connected with the live oil filtering pipeline through a lead and a sensor, when the live oil filtering pipeline leaks, the voltage monitor, the lead, the sensor and the live oil filtering pipeline are connected to form a new loop, and the voltage monitor detects the voltage change of the pipeline at the moment, so that the live oil filtering pipeline is found to leak; the voltage monitors are uniformly distributed on the electrified oil filtering pipeline;
s6: monitoring the liquid level, detecting the liquid level change in the oil drain tank, judging whether the liquid in the oil drain tank exceeds a preset threshold value, and displaying prompt information if the liquid exceeds the preset threshold value; detecting the liquid level change in the oil drainage tank by a liquid level monitor, continuously sending out ultrasonic waves by the liquid level monitor, wherein the ultrasonic waves are reflected by contacting with the liquid in the oil drainage tank, and obtaining the liquid level change in the oil drainage tank after the liquid level monitor receives the ultrasonic waves; most people install an oil drain tank at a point where the oil filter pipeline is easy to leak, so that loss of the oil filter pipeline is reduced when the oil filter pipeline leaks, liquid is led into the oil drain tank to change the liquid level of the oil drain tank, and then the liquid level monitoring meter is used for carrying out early warning;
s7: data enhancement, namely reducing transmission pressure of detection information of the electrified oil filtering pipeline; the transmission speed of the wireless network is improved through a wireless network signal enhancer; the data medium-speed point is arranged between the detection equipment and the server, and the data is compressed through the medium-speed point, so that the pressure of data network information transmission is reduced;
s8: data statistics is carried out according to a preset standard, and a map and a table are formed; when the data is counted, the data is counted according to unit information management, user information management and authority information management, so that a daily chart, a weekly chart, a monthly chart, a quarterly chart and a yearly chart are formed; the unit information management comprises data sources of all units, users and shared data source configuration information, operation logs of all users are inquired through user information management, operation processes of the users are audited, operation authorities of the units and the users are controlled through authority information management, the authority information management is analyzed by a super manager, sub-authority distribution is carried out according to analysis results, and visual reaction detection data of daily charts, weekly charts, monthly charts, quarterly charts and annual charts are utilized, so that the manager can conveniently observe; and importing the statistical data into a database; thus, the high-precision monitoring of parameters such as the flow, pressure, gas content and the like of the insulating oil at the inlet and the outlet of the transformer is realized;
s9: data storage, namely importing the counted atlas and table into a database for storage; the data storage is carried out through the storage server, and the server is a permanent server, so that the data loss is prevented; the data storage is classified according to preset indexes, most of the indexes are temperature, pressure, density and viscosity, and the data storage also comprises public data storage and private data storage, and the public storage module network hard disk stores data of each stage of management circulation of the charged oil filtering pipeline; the stored data is subjected to data modeling and encryption according to a unique algorithm in the unit, and a secret key formed by encryption is issued according to the management authority;
s10: comparing the graphs, firstly calling the past date data in the database to make a data model, and then comparing the data model with the current graphs and tables in real time; the database is accessed remotely, so that data real-time calling is realized, and a called data model needs special key unlocking for encryption data; the keys which are registered differently are only owned by the manager of the corresponding level, so that the risk of data leakage is reduced, the historical data of the online data model is compared with the historical data of the data model in real time, abnormal signals are immediately sent out when the data exceeds a threshold value, and signals of different levels are sent out according to the difference value of chart comparison; by carrying out automatic comparison calculation on each monitoring data, judging whether oil leakage exists in oil treatment systems such as an oil filter and the like, and automatically commanding and controlling the correct operation of the systems; the method avoids the serious environmental and safety accidents caused by the large amount of leakage of the transformer oil; the unified database can be used for quickly searching the target data, so that a great amount of labor and time cost is saved, and after the pipeline data is compiled, the historical data in the database are called for comparison, so that the pipeline leakage position can be quickly found, and the speed and accuracy of pipeline leakage monitoring are improved;
s11: an alarm is sent out, and when the leakage of the electrified oil filtering pipe is found through online real-time comparison, an alarm notification is immediately sent out to the management platform and the mobile terminal; when the leakage of the electrified oil filtering pipeline is found, the audible and visual alarm gives out sound and flashing, so that the leakage of the pipeline of the field staff is reminded; and the leakage signal is sent to the management platform and the mobile terminal of the manager through the wireless network, the slight pipeline leakage is just a notification message, and the serious pipeline leakage sending alarm page directly covers the display screen of the management platform, so that the mobile phone interface of the manager mobile terminal can remind people of serious leakage of the electrified oil filtering pipeline.
In summary, when the online live oil filter pipeline leakage detection method for the large transformer is used, the approximate situation of the live oil filter pipeline is checked and maintained, then the threshold value of detection equipment is set according to the actual situation of the live oil filter pipeline, the temperature, pressure, density and viscosity change situation of fluid substances in the monitoring pipeline are detected simultaneously when the fluid substances run along the pipeline, the monitored result is transmitted to a database through a wireless network, the database carries out data statistics according to preset standards, the data is transmitted to a storage server after the data statistics is completed, the server carries out data modeling on the stored data according to a unique algorithm to form comparison data, then people carry out online comparison on a chart formed by the data monitored at present, find out that the data exceeds the threshold value immediately, send out abnormal signals according to the difference value of the chart comparison, send different grades of signals, severe pipeline leakage send alarm pages directly cover a display screen of a management platform, a mobile phone interface of a manager mobile terminal, thereby reminding people of serious leakage of the live oil filter pipeline, further can quickly find out the position of the pipeline leakage, the pipeline leakage is improved, the monitoring speed of the pipeline is accurately compared with the monitoring pipeline, the follow-up leakage is similar to the detailed description of the prior art, and the leakage detection method is similar to the prior art.
Although the present invention has been described with reference to the foregoing embodiments, it will be apparent to those skilled in the art that modifications may be made to the embodiments described, or equivalents may be substituted for elements thereof, and any modifications, equivalents, improvements and changes may be made without departing from the spirit and principles of the present invention.
Claims (10)
1. The online live oil filtering pipeline leakage detection method for the large transformer is characterized by comprising the following steps of:
s1: checking and maintaining, namely checking and maintaining the electrified oil filtering pipeline through regular inspection of staff;
s2: setting a reference, and setting a threshold value of detection equipment according to the actual condition of the electrified oil filtering pipeline;
s3: flow monitoring, namely detecting inflow and outflow of liquid in the electrified oil filtering pipeline, judging whether the flow deviation rate exceeds a preset threshold value, and displaying prompt information if the flow deviation rate exceeds the preset threshold value;
s4: temperature monitoring, namely detecting temperature change in the electrified oil filtering pipeline, judging whether the temperature deviation exceeds a preset threshold value, and displaying prompt information if the temperature deviation exceeds the preset threshold value;
s5: voltage monitoring, namely detecting voltage change of the electrified oil filtering pipeline, judging whether the voltage deviation exceeds a preset threshold value, and displaying prompt information if the voltage deviation exceeds the preset threshold value;
s6: monitoring the liquid level, detecting the liquid level change in the oil drain tank, judging whether the liquid in the oil drain tank exceeds a preset threshold value, and displaying prompt information if the liquid exceeds the preset threshold value;
s7: data enhancement, namely reducing transmission pressure of detection information of the electrified oil filtering pipeline;
s8: data statistics is carried out according to a preset standard, and a map and a table are formed;
s9: data storage, namely importing the counted atlas and table into a database for storage;
s10: comparing the graphs, firstly calling the past date data in the database to make a data model, and then comparing the data model with the current graphs and tables in real time;
s11: and sending out an alarm, and immediately sending out an alarm notification to the management platform and the mobile terminal when the live oil filtering pipe is found out to be leaked by online real-time comparison.
2. The method for detecting leakage of the online live oil filtering pipeline of the large transformer according to claim 1, which is characterized by comprising the following steps of: in the step S3, the inflow and outflow of the liquid in the live oil filtering pipeline is monitored by the mass-volume balance method in combination with the ultrasonic flowmeter, when the difference value in the live oil filtering pipeline is greater than a certain range, the detected pipeline is indicated to be likely to leak, and the information of the leakage of the monitored pipeline is transmitted through a wireless network.
3. The method for detecting leakage of the online live oil filtering pipeline of the large transformer according to claim 1, which is characterized by comprising the following steps of: in the step S4, the temperature change in the live oil filter pipeline is monitored by a pipeline temperature monitor, and the error is reduced by multipoint temperature detection in the designated area.
4. The method for detecting leakage of the online live oil filtering pipeline of the large transformer according to claim 1, which is characterized by comprising the following steps of: in the step S5, the voltage monitor monitors the voltage change in the live oil filter pipeline, and the voltage monitor is connected with the live oil filter pipeline through a wire and a sensor, when the live oil filter pipeline leaks, the voltage monitor, the wire, the sensor and the live oil filter pipeline are connected to form a new loop, so that the leakage of the live oil filter pipeline is found.
5. The method for detecting leakage of the online live oil filtering pipeline of the large transformer according to claim 1, which is characterized by comprising the following steps of: in step S6, the liquid level monitor continuously sends out ultrasonic waves to detect the liquid level change in the oil drain tank, and the ultrasonic waves are reflected by contacting with the liquid in the oil drain tank, so that the liquid level change in the oil drain tank is known.
6. The method for detecting leakage of the online live oil filtering pipeline of the large transformer according to claim 1, which is characterized by comprising the following steps of: in step S7, the transmission speed of the wireless network is increased by the wireless network signal enhancer.
7. The method for detecting leakage of the online live oil filtering pipeline of the large transformer according to claim 1, which is characterized by comprising the following steps of: in the step S8, the data statistics is performed according to the unit information management, the user information management, and the authority information management, so as to form a daily chart, a weekly chart, a monthly chart, a quarterly chart, and a yearly chart.
8. The method for detecting leakage of the online live oil filtering pipeline of the large transformer according to claim 1, which is characterized by comprising the following steps of: in step S9, the data storage is performed by the storage server, and the server is a permanent server, so as to prevent data loss.
9. The method for detecting leakage of the online live oil filtering pipeline of the large transformer according to claim 1, which is characterized by comprising the following steps of: in step S10, the database is accessed remotely, so that the data is invoked in real time, and the invoked data model requires a special key for unlocking the encrypted data.
10. The method for detecting leakage of the online live oil filtering pipeline of the large transformer according to claim 1, which is characterized by comprising the following steps of: in the step S11, when the leakage of the live oil filtering pipeline is found, the audible and visual alarm is used for sounding and flashing, so that the leakage of the live working personnel pipeline is reminded.
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| CN202310949203.4A CN116951330A (en) | 2023-07-29 | 2023-07-29 | Large transformer online live oil filtering pipeline leakage detection method |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117870775A (en) * | 2024-03-11 | 2024-04-12 | 山东港源管道物流有限公司 | Storage tank detection system and method based on intelligent oil depot |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117870775A (en) * | 2024-03-11 | 2024-04-12 | 山东港源管道物流有限公司 | Storage tank detection system and method based on intelligent oil depot |
| CN117870775B (en) * | 2024-03-11 | 2024-05-14 | 山东港源管道物流有限公司 | Storage tank detection system and method based on intelligent oil depot |
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