CN111754372A - Hydropower station flooded workshop accident perception decision-making command system based on Internet of things - Google Patents
Hydropower station flooded workshop accident perception decision-making command system based on Internet of things Download PDFInfo
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Abstract
The invention provides a hydropower station flooded workshop accident perception decision-making command system based on the Internet of things, which consists of a decision-making command center server, a core switch, an access controller, a fire-fighting controller, a broadcast controller, a computer monitoring system, a personnel positioning server, an information pushing server, a water level camera and a liquid level transmitter.
Description
Technical Field
The invention relates to a hydropower station flooded workshop accident perception decision-making command system based on the Internet of things, which is suitable for the field of hydroelectric power generation.
Background
A flooded workshop is the most harmful one in an emergency accident of a hydropower station, and the safe operation of the hydropower station and the safety of a power grid are seriously influenced. At present, most hydropower stations are provided with a water flooded workshop alarming and early warning device, on-duty workers report layer by layer when an accident occurs, emergency guidance such as plant equipment control, entrance guard control, fire control, evacuation and evacuation is manually carried out, the feedback efficiency is low, and major personal injury and economic loss are easily caused if on-duty careless omission occurs.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: the utility model provides a power station water logging factory building accident perception decision-making command system based on thing networking, automatic accident information notice responsible person at all levels, automatic control equipment, entrance guard, fire control, broadcasting etc. system are sent to automatic statistics evacuation personnel quantity and position, improve the timeliness and the high efficiency of power station accident handling.
The technical scheme adopted by the invention is as follows: a hydropower station flooded workshop accident perception decision-making command system based on the Internet of things is characterized by comprising a decision-making command center server, a core switch, an access controller, a fire-fighting controller, a broadcast controller, a computer monitoring system, a personnel positioning server, an information pushing server, a water level camera and a liquid level transmitter, wherein the access controller, the fire-fighting controller, the broadcast controller, the computer monitoring system, the personnel positioning server, the information pushing server, the water level camera and the liquid level transmitter are connected with the core switch through optical fibers, and the core switch is connected with the decision-making command center server through the optical fibers;
the liquid level transmitter and the water level camera are flooding factory accident sensing equipment, and the liquid level transmitter transmits the water level and the water level rising rate to the decision command center server in real time through the core switch; the water level camera sends the water level picture to a decision command center server in real time through a core switch;
the decision command center server is a flood workshop accident decision command device and is internally provided with a decision algorithm model, a command algorithm model, a water level recognition algorithm model, a personnel statistics algorithm model, a database and a data interface program; and receiving the water level, the water level rising rate, the water level image and the personnel positioning data, and sending a command control instruction.
Further, the decision algorithm model is a mathematical function model, the model consists of a water level threshold and a water level rising rate threshold, and whether an accident occurs is judged according to the threshold.
Furthermore, the command algorithm model is a linkage relation model and consists of system control instructions; and according to the decision algorithm model judgment result, automatically matching the linkage relation, and sending an entrance guard control instruction, a fire control instruction, a broadcast control instruction, a computer monitoring system control instruction and an information push control instruction.
Further, the water level recognition algorithm is an image recognition algorithm and is used for recognizing the real-time position of the water level according to the water level picture and providing data input for the decision algorithm model.
Further, the personnel statistical algorithm model is a mathematical function model, real-time position data of the staff are uploaded to the decision command center server through the RFID staff card, the personnel positioning server and the core switch, and the personnel statistical algorithm model automatically counts the number and the positions of the evacuated staff.
Further, the database is a time sequence database and stores water level data, water level rising rate data and water level image data.
Furthermore, the data interface program is a widely applied power internet of things multi-protocol data interface program, wherein the data acquisition uses RFID and RS485 interfaces, the data call between models adopts Web Service and restful interfaces, and the data call between devices adopts Web Service and restful interfaces.
The information pushing server is accident alarm equipment and can push accident information and personnel positioning statistical information to operation and maintenance responsible persons, duty master and officers, quality department responsible persons, companies, branch management and leaders and whole plant staff in real time.
The personnel positioning server is personnel positioning statistical equipment, and data is acquired from an RFID employee card worn by an employee.
And the computer monitoring system receives the command of the decision command center server to control the accident shutdown and drop accident valve of the unit.
And the broadcast controller receives the command of the decision command center server to carry out factory wide accident broadcast alarm.
And the fire-fighting controller receives an instruction of the decision command center server to start accident fire fighting.
And the entrance guard controller receives an instruction of the decision command center server to open the escape route entrance guard.
The invention has the beneficial effects that: utilize electric power internet of things and multisystem linkage, realize that power station water logging factory building accident intelligence decision-making guides, send accident information notice responsible person at all levels automatically, system such as automatic control equipment, entrance guard, fire control, broadcasting, the sparse personnel quantity of automatic statistics and position improve the promptness and the high efficiency of power station incident treatment, will provide help for the incident treatment and the safe operation of power station.
Drawings
FIG. 1 is a schematic diagram of the system of the present invention.
FIG. 2 is a schematic diagram of the perceptual decision logic of the present invention.
Detailed Description
Referring to fig. 1, the hydropower station flooded workshop accident sensing decision-making command system based on the internet of things in the embodiment is composed of a decision-making command center server 1, a core switch 2, an access controller 3, a fire controller 4, a broadcast controller 5, a computer monitoring system 6, a personnel positioning server 7, an information pushing server 8, a water level camera 9 and a liquid level transmitter 10. The access controller 3, the fire-fighting controller 4, the broadcast controller 5, the computer monitoring system 6, the personnel positioning server 7, the information pushing server 8, the water level camera 9 and the liquid level transmitter 10 are connected with the core switch 2 through optical fibers, and the core switch 2 is connected with the decision-making command center server 1 through the optical fibers.
The sensors of the liquid level transmitter 10 and the water level camera 9 are arranged on an overhaul layer of an underground powerhouse of the hydropower station, the fire-fighting controller 4 is arranged in a fire room of the underground powerhouse of the hydropower station, the broadcast controller 5 and the access controller 3 are arranged in a comprehensive control room of the underground powerhouse of the hydropower station, and the information push server 8, the personnel positioning server 7, the computer monitoring system 6, the core switch 2 and the decision-making command center server 1 are arranged in an information machine room.
The decision command center server is a flood workshop accident decision command device, is internally provided with a decision algorithm model, a command algorithm model, a water level identification algorithm model, a personnel statistics algorithm model, a database and a data interface program, receives water level, water level rising rate, water level image identification and personnel positioning data, and sends command control instructions.
The 375MW pumped-storage hydropower station is taken as an example to illustrate the specific implementation mode of the invention. According to the logic diagram of perceptual decision shown in fig. 2, the specific implementation is as follows:
the liquid level transmitter 10 collects the overall water level data of the factory building and calculates the water level rising rate, and the water level data and the water level rising rate are sent to the decision-making command center server 1 through the core switch 2 in real time. The water level camera 9 sends the water level picture to the decision command center server 1 in real time through the core switch 2.
The decision command center server 1 receives the water level data and the water level rising rate data of the liquid level transmitter 10, and if the real-time water level exceeds the alarm water level or the water level rising rate exceeds a threshold value, for example, the water level rising rate calculated by the water level data at multiple moments is 24cm/min and exceeds an enterprise standard threshold value of 23.3 cm/min; and the decision command center server 1 receives the water level picture shot by the water level camera 9, and verifies that the whole water level of the plant rises to the bottom end of the generator stator bar through image recognition and analysis. And integrating the data, and sensing the occurrence of the factory building accident of the hydropower station by the decision command center server 1. Meanwhile, the core exchanger respectively sends an access control command to the access controller 3, a fire control command to the fire controller 4, a broadcast control command to the broadcast controller 5, a control command to the computer monitoring system 6 and an information push control command to the information push server 8.
And the information pushing server 8 receives the instruction of the decision-making command center server 1, and pushes accident information and personnel positioning statistical information to operation and maintenance responsible persons, duty master and officers, safety department responsible persons, companies, branch management leaders and whole plant employees in real time. The personnel positioning statistical information is collected and sent by a personnel positioning server 7, and the data is collected from an RFID employee card worn by an employee. Real-time position data of staff are uploaded to a decision command center server 1 through an RFID staff card, a staff positioning server 7 and a core switch 2, the number and the positions of evacuated staff are automatically counted through a staff counting algorithm model, and a counting result is sent to an information pushing server 8 through the core switch 2.
And the computer monitoring system 6 receives the command of the decision command center server 1 to control the unit emergency accident shutdown, the emergency falling warehouse-in accident gate and the emergency falling warehouse-out accident gate.
And the broadcast controller 5 receives the instruction of the decision command center server 1 to carry out factory-wide accident broadcast alarm.
The fire-fighting controller 4 receives the command of the decision-making command center server 1 to start accident fire fighting.
And the access controller 3 receives the instruction of the decision-making command center server 1 to open the escape route access control.
The above-described embodiments are intended to illustrate the present invention, but not to limit the present invention, and any modifications, equivalents, improvements, etc. made within the spirit of the present invention and the scope of the claims fall within the scope of the present invention.
Claims (9)
1. A hydropower station flooded workshop accident perception decision-making command system based on the Internet of things is characterized by comprising a decision-making command center server, a core switch, an access controller, a fire-fighting controller, a broadcast controller, a computer monitoring system, a personnel positioning server, an information pushing server, a water level camera and a liquid level transmitter, wherein the access controller, the fire-fighting controller, the broadcast controller, the computer monitoring system, the personnel positioning server, the information pushing server, the water level camera and the liquid level transmitter are connected with the core switch through optical fibers, and the core switch is connected with the decision-making command center server through the optical fibers;
the liquid level transmitter and the water level camera are flooding factory accident sensing equipment, and the liquid level transmitter transmits the water level and the water level rising rate to the decision command center server in real time through the core switch; the water level camera sends the water level picture to a decision command center server in real time through a core switch;
the decision command center server is a flood workshop accident decision command device and is internally provided with a decision algorithm model, a command algorithm model, a water level recognition algorithm model, a personnel statistics algorithm model, a database and a data interface program; and receiving the water level, the water level rising rate, the water level image and the personnel positioning data, and sending a command control instruction.
2. The hydropower station flooded building accident sensing decision-making command system based on the internet of things as claimed in claim 1, wherein the decision-making algorithm model is a mathematical function model, the model is composed of a water level threshold and a water level rising rate threshold, and whether an accident occurs or not is judged according to the threshold.
3. The Internet of things-based hydropower station flooded workshop accident sensing decision-making command system is characterized in that the command algorithm model is a linkage relation model, and the model consists of system control instructions; and according to the decision algorithm model judgment result, automatically matching the linkage relation, and sending an entrance guard control instruction, a fire control instruction, a broadcast control instruction, a computer monitoring system control instruction and an information push control instruction.
4. The Internet of things-based hydropower station flooded building accident sensing decision-making command system as claimed in claim 1, wherein the water level recognition algorithm model is an image recognition algorithm model for recognizing a water level real-time position according to a water level picture and providing data input for the decision-making algorithm model.
5. The Internet of things-based hydropower station flooded building accident sensing decision-making command system as claimed in claim 1, wherein the database is a time sequence database, and stores water level data, water level rising rate data and water level image data.
6. The Internet of things-based hydropower station flooded building accident sensing decision-making command system as claimed in claim 1, wherein the data interface program is an electric Internet of things multi-protocol data interface program for data acquisition, data call between models and data call between devices.
7. The hydropower station flooded building accident sensing decision-making command system based on the internet of things as claimed in claim 1, wherein the information pushing server is an accident alarm device capable of pushing accident information and personnel positioning statistical information to operation and maintenance responsible persons, duty masters and officers, quality department responsible persons, companies and branch management leaders, and plant employees in real time.
8. The Internet of things-based hydropower station flooded building accident sensing decision-making command system as claimed in claim 1, wherein the personnel positioning server is personnel positioning statistical equipment, and data is acquired from an RFID employee card worn by an employee.
9. The Internet of things-based hydropower station flooded workshop accident sensing decision-making command system as claimed in claim 1, wherein the personnel statistical algorithm model is a mathematical function model, real-time position data of staff is uploaded to the decision-making command center server through an RFID (radio frequency identification) staff card, a personnel positioning server and a core switch, and the personnel statistical algorithm model automatically counts the number and the positions of evacuated staff.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113701843A (en) * | 2021-07-09 | 2021-11-26 | 国网浙江省电力有限公司温州供电公司 | Water logging on-line monitoring system |
| CN117953666A (en) * | 2024-03-27 | 2024-04-30 | 南京金固智慧市政研究院有限公司 | Flooding early warning monitoring system based on image recognition for easily flooded and easily waterlogged areas |
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| CN108093223A (en) * | 2017-12-28 | 2018-05-29 | 合肥云弘测控科技有限公司 | Power generation safety monitoring system and its control method |
| CN208588439U (en) * | 2018-07-20 | 2019-03-08 | 中国长江电力股份有限公司 | A kind of water logging workshop alarm system based on computer supervisory control system |
| CN110106964A (en) * | 2019-07-03 | 2019-08-09 | 广东电网有限责任公司佛山供电局 | A kind of intelligent drainage function aid decision-making system for low-lying substation |
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2020
- 2020-05-13 CN CN202010400003.XA patent/CN111754372A/en active Pending
Patent Citations (4)
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| CN104102202A (en) * | 2014-07-08 | 2014-10-15 | 国网辽宁省电力有限公司 | Modernized smart grid-based regulation and control emergency command handling method |
| CN108093223A (en) * | 2017-12-28 | 2018-05-29 | 合肥云弘测控科技有限公司 | Power generation safety monitoring system and its control method |
| CN208588439U (en) * | 2018-07-20 | 2019-03-08 | 中国长江电力股份有限公司 | A kind of water logging workshop alarm system based on computer supervisory control system |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113701843A (en) * | 2021-07-09 | 2021-11-26 | 国网浙江省电力有限公司温州供电公司 | Water logging on-line monitoring system |
| CN117953666A (en) * | 2024-03-27 | 2024-04-30 | 南京金固智慧市政研究院有限公司 | Flooding early warning monitoring system based on image recognition for easily flooded and easily waterlogged areas |
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